2D Guidance in Minimally Invasive Procedures

2D Guidance in Minimally Invasive Procedures Research Strategy (a) SIGNIFICANCE: The use of two-dimensional (2D) Ultrasound (US) guidance in minimally invasive procedures such as percutaneous biopsies,1,2 pain management,3,4 abscess drainages,5 and radiofrequency ablation6 has gained popularity. These procedures all involve insertion of a needle towards a desired anatomical target. Image-guidance facilitates localization of the needle throughout the procedure, increasing accuracy, reliability and safety.7 US offers several advantages over other imaging modalities traditionally used in interventional radiology such as fluoroscopy, magnetic resonance imaging (MRI) and computed tomography (CT): It provides real-time visualization of the patients anatomy (including soft tissue and blood vessels) vis-à  -vis the needle, without exposure to ionizing radiation.8 Additionally, being portable and low cost (compared to other imaging modalities) are the added advantages of US imaging. Despite these advantages, the effectiveness of 2D US in needle guidance is highly operator dependent. In the in-plane approach, where needle shaft is parallel to the imaging plane, the needle shaft and tip should ideally be continually visible.9 However, aligning the needle shaft with the scan plane is difficult. Even when the needle is properly aligned, steep orientation (required in most procedures) of the needle with respect to the US beam causes nonaxial specular reflection of the US signal off the needle surface due to a large angle of incidence.10 In this imaging condition, the needle shaft will appear discontinuous and/or the tip will be invisible. This scenario is common with deep targets, for example during liver biopsies and epidural blocks. The challenge of needle visibility at increasing depths is compounded by attenuation of the US signal. Further, high intensity soft tissue artifacts, acoustic shadowing from dense structures such as bone and speckle noise obstruct needl e visibility. To recover needle visibility, clinicians conduct transducer manipulation by translation or rotation, movement of the needle to and fro (pump maneuver),11 stylet movement, needle rotation, and hydrolocation.12 These techniques are variable and subjective. An invisible needle can have detrimental effects on procedures, for example, reduced procedure efficacy, increase in procedure duration, neural, visceral or vascular injury, and infection. Diagnostic accuracy of 90-95% has been reported for US guided breast biopsies,13-15 and 83-95% for US guided liver biopsies.16 It is known that targeting errors due to insufficient needle tip visualization contribute to false negative results.17 In pain management, accidental intraneural injections have been reported in 17% of ultrasound-guided upper- and lower-extremity blocks, even when the procedures were conducted by expert anesthesiologists.18,19 Most of these arise because of poor needle tip localization, which makes it difficu lt to distinguish between subfascial, subepineural, or intrafascicular injections.20 In our ongoing work, we have developed an algorithm for needle enhancement and tip localization in 2D US. This, we achieved by modelling transmission of the US signal.21 We incorporated US signal modeling into an optimization problem to estimate an unknown signal transmission map, which was then used to enhance the needle shaft and tip while considering US specific signal propagation constraints.22 Automatic tip localization was achieved using spatially distributed image statistics limited to the trajectory region. However, incorrect tip localization occurred when high intensity soft tissue interfaces were present along the needle trajectory. The algorithm also required a visible portion of the shaft close to the transducer surface, necessitating proper alignment of the needle with the scan plane. We have also conducted preliminary work on needle detection and enhancement in three-dimensional (3D) US, a modality with potential to obviate the limitations of 2D US in needle guidance. Instead of the latters planar view (one slice at a time), 3D US displays volume data, allowing better visualization of anatomy and needle trajectory at all needle axis orientations. This alleviates the challenge of needle alignment in the scan plane.23 Nevertheless, needle obliquity at steep insertion angles, depth dependent attenuation, as well as acoustic shadowing, imaging artifacts and speckle remain.24,25 Needle visibility is also affected by low dimension of the needle with respect to the US volume. In fact, reported false-negative results for breast biopsies under 3D US show no improvement over those with 2D US.26,27. Consequently, 3D US has not replaced 2D US as the standard of care. To overcome the limitations, researchers have proposed computational methods for needle enhancement and local ization in 3D US. These include: Principal component analysis based on eigen-decomposition,28 the 3D Hough transform,29 the 3D Radon transform,30 parallel integration projection,31 and iterative model-fitting methods such as random sample consensus (RANSAC)32. The accuracy of these methods is affected by attenuation and high intensity artifacts. Besides, computational complexity arises from processing the large amount of volume data.33 Projection based methods fail when a good portion of the shaft is not visible and the tip intensity is low. A more robust needle localization framework based on oscillation of a stylus was recently proposed, although it fails in a single operator scenario, especially for shallow angles.34 All the mentioned methods are based on modeling B-mode image data. The current need, in interventional radiology for needle guidance, is a cost-effective, easy to use, non-radiation based real-time imaging platform with an ability of providing continuous guidance with high accuracy during needle insertion without intercepting the clinical workflow. Our long-term goal of developing a computational 3D US based imaging platform for enhancement and localization of needles is informed by this need. To address this pressing need, we hypothesize that automatic, real-time, accurate, and continuous target identification using 3D radiofrequency (RF) US data is feasible and potentially could be used to provide guidance during interventional radiology for needle insertion.Our preliminary work on modeling US signal transmission in 2D US, as well as needle detection and enhancement in 3D US, are strongly supportive that modeling the RF US signal coupled with advanced reconstruction methods will improve needle visualization and localization in 3D US. The envisaged 3D US reconstruction techniques will incorporate emerging work from machine learning and advanced beamforming to achieve needle enhancement and localization. We envision new pathways of processing and presenting US data, which should make this rich modality ubiquitous to all end-users for needle guidance in interventional radiology. The impact of the proposal will be multiplied since the developed algorithms, using open-source software platform, can also be incorporated as a stand-alone component into existing US imaging platforms. (b) INNOVATION: Previous work on needle enhancement has mostly been focused on enhancement of B-mode images. B-mode images are derived from RF data (the raw signal backscattered onto the US transducer) after several proprietary processing steps. The raw signal is known to contain more statistical information35 which is lost along the processing pipeline. Parallel integral projection in order improve needle visibility in soft tissues using 2D and 3D RF data has previously been investigated although no image visualization, needle enhancement or localization was demonstrated.36 It has been shown that the post-beamformed 2D RF signal allows for a more improved enhancement of local features in US images. 37,38 Image enhancement methods applied to RF signal have also shown to produce improved display of orientation of a biopsy needle.37,38 This study is innovative in three respects: 1) To the best of our knowledge, it is the first to investigate needle enhancement and localization from 3D pre-beamformed RF data (previous approaches were using post-beamformed RF information). 2) The utilization of machine learning approaches, such as deep learning for needle enhancement in 3D US will be a first. 3) Although this pilot will focus on validating the developed framework on pain management and liver biopsy procedures as a case study, the new mathematical and computational approaches proposed in this work will lead to developments that can easily be adopted for enhancement and localization of needles in other interventional radiology procedures. We expect that the achieved results will lead in gradual adoption of 3D US as the standard of care in problematic minimally invasive procedures where 2D US is challenged, thus improving therapeutic and diagnostic value, reducing morbidity and optimizing patient safety. (c) APPROACH: We propose to test the hypothesis that needle detection, enhancement and localization based on the raw 3D RF signal will provide a more accurate and robust platform for needle guidance than current state of the art. The basis for this hypothesis is found by precedent in the use of the RF signal for bone localization,39 and our published21,22 and unpublished work on needle enhancement and localization based on 2D/3D B-mode image data. This preliminary data is presented below. Preliminary work 1 Modeling 2D US signal transmission for Needle Shaft and Tip Enhancement When the US signal pulses are sent by the transducer into tissue, they undergo reflection, scattering, absorption and refraction. These phenomena all contribute to attenuation; the loss in intensity of the US pulses as they travel deeper into tissue. Attenuation is responsible for non-conspicuity of the needle tip and shaft at increasing depths. Previously, we have shown that modeling signal transmission in 2D US based on 2D image data, while considering depth-dependent attenuation leads to enhancement of the needle and more accurate tip localization.21 The modelling framework yields signal transmission maps, which are then used in an image-based contextual regularization process to achieve tip and shaft enhancement (Fig.1). A tip localization accuracy of mm was achieved in ex vivo tissue. However, the localization accuracy is lower when soft tissue interfaces are present along the needle trajectory, and when the needle is not properly aligned in the scan plane. In the context of th is proposal, our objective is to apply similar US signal modeling and contextual regularization, this time based on RF data. Preliminary work 2 Machine learning approaches for needle detection and enhancement in 3D US Since 3D US is multiplanar, the challenge associated with needle alignment in the scan plane is partially eliminated when it is used in needle guidance.   Nevertheless, 3D US is also affected by US signal attenuation. Previous methods proposed for needle enhancement and localization in 3D US did not address this need. In addition, most were computationally demanding because of the requirement to process the entire US volume. In this work (results submitted to 20th MICCAI conference, 2017), we have developed a learning-based method for automatic needle detection in 3D US volumes. The pixel-wise classifier generates a sub-volume containing only slices with needle information. In so doing, computational complexity on the subsequent enhancement and localization algorithms is reduced (Fig.2). The tip is automatically localized in 3D. We achieved 88% detection precision, 98% recall rate, a slice classification time of 0.06 seconds, a localization accuracy of mm, and a training time of 1 5 seconds. Figure 2. Learning based needle detection, enhancement and localization in 3D US. Top row: an example of needle detection. Here, the original volume contained 41 slices, and the classifier identified only 7 containing needle data. Bottom row: The enhancement process on the sub-volume. Left, enhanced intensity projection image. Middle, automatically localized tip (red) displayed on the relevant axial slice. The blue cross is the manually localized tip. Right, trajectory estimation indicated by the green line. Specific Aim 1. To develop RF-signal modeling algorithms for improved 3D US image reconstruction For this aim, we hypothesize that adaptive beamforming methods applied to pre-beamformed 3D RF data will enhance needle visibility and improve quality of US volumes. During the formation of an US image, the reflected US signals are received by the transducer elements at different time points due to varying signal travel distances. Beamforming on each scan line is meant to establish signal synchronism before aggregation. The conventional method of beamforming in both 2D and 3D US is delay and sum (DAS). Here, received signals are electronically delayed, followed by application of a beamformer whose weights are reliant on echo signals, leading to undesirable wide main-lobe and high side-lobe levels resulting in imaging artifacts, thus decreasing the image resolution and contrast. 40 In this architecture, the angular resolution is dependent on the length of the scan aperture and the fixed operating frequency.41 In a fixed hardware configuration, these parameters cannot be increased, hen ce resolution cannot be improved. To overcome this challenge, adaptive beamforming methods based on minimum variance42-45 and multi-beam covariance matrices46 have been proposed. Using adaptive beamformers signal detection can be maximized while minimizing the beam-width and side lobe artifacts.47,48 Recently, phase factor beamforming, where phase variations are tracked across the receive aperture domain, has been shown to improve the appearance of bone surfaces from 2D US data49. Bone features, similar to needle features, are hyper-echoic when imaged with US. Therefore, during this aim we will develop an adaptive phase-factor beamforming method in order to enhance the hyper-echoic targets such as the needle from 3D pre-beamformed RF data. Specifically, adaptive beamformer that combines ideas from Minimum Variance (MV) adaptive beamforming,50 signal regularization based on statistical information in RF data,51 and Toeplitz structure covariance matrices52 to minimize computational co mplexity will be investigated. It is expected that this reconstruction technique will adapt the data to the clinical application of needle enhancement through improving image resolution, contrast, and speckle suppression. The algorithms will be incorporated into an open source imaging platform for real-time data collection and processing.   Ã‚  Ã‚   Overall, we expect that the algorithms developed in Aim 1 will allow enhanced representation of US needle data with increased diagnostic value. The images obtained from this aim will be used as an input to the algorithms proposed in Aim2. Specific Aim 2. To develop methods for needle enhancement and tip localization in 3D US images Our working hypothesis for this aim is that learning based approaches for needle detection coupled with image reconstruction methods in 3D US will achieve improved needle enhancement and tip localization. In our previous work, we have shown that a linear learning based pixel classifier for needle data in 3D US, based on local phase based image projections, improves needle enhancement and reduces computational load.   The detector utilizes Histogram of Oriented Gradients (HOG)53 descriptors extracted from local phase projections and a linear support vector machine (SVM) baseline classifier. Recently, deep learning (convolutional neural network (CNN)) based image processing approaches have shown to produce very accurate results for segmentation of medical image data54. However, enhancement or segmentation of needles from US data using convolutional neural networks has not been investigated yet.   Therefore, for during this aim we will develop a needle enhancement and segmentation m ethod using convolutional neural networks. Needle images with various insertions angles and depths will be labeled by an expert radiologist. Our clinical collaborator Dr. Nosher and several radiologists from RWJMH will be involved during this labeling process. We will use two different datasets during the labeling process. The first data set will be retrospective US images downloaded from the Robert Wood Johnson Medical Hospital (RWJMH) database. Specific focus will be given to liver biopsy and epidural management procedures where US has been used to guide the needle insertion and biopsy procedure. The second data set will involve collecting needle US scans using ex vivo tissue samples as the imaging medium. These scans will be collected at the PIs laboratory using an open source platform US machine with 3D imaging capabilities. The collected ex vivo data will be enhanced using the beamforming methods developed in Aim 1.   Labeling process will involve manual identification of the needle tip and shaft from the two datasets. A fully convolutional neural network54 will be trained using the labeled data. The architecture of this network does not require extensive data sets in order to train the network and yields high segmentation results. Previously this approach was used for segmenting cell structures54. The output of this operation, which will be a fuzzy 3D probability map (high probability regions corresponding to needle interface), will be used as an input to our previously developed needle tip localization method. The automatically identified needle tips will be compared against the manually identified needle tips. More details about the specific clinical data collection and validation are provided in Specific Aim 3 and Protection of Human Subjects. Overall, at the end of Aim 2 we expect to have a system providing continuous real-time monitoring of needle insertion using 3D US for improved guidance in interventional radiology procedures. Specific Aim 3. To validate the developed imaging platform on clinical data To validate the algorithms developed in Aims 1-2, we plan to perform extensive validation on ex vivo and clinical data. No clinical trial will be conducted during this proposal. Our initial validation will be limited to epidural administration and liver biopsy procedures. Ex vivo data: This study will be conducted for validating Aims 1-2. US scans will be collected from two different needles: 1-) A general 17-gauge Tuohy epidural needle (Arrow International,Reading, PA, USA),   and 2-) 18-gauge biopince full core liver biopsy needle (Argon Medical devices, Athens, Texas, USA). The needles will be inserted at varying insertion angles (300−700) and depths (up to 12 cm). Ex vivo porcine, bovine, liver, kidney and chicken tissue samples will be used as the imaging medium. 3Dpre-beamformed RF data will be collected using a SonixTouch US system (Analogic Corporation, Peabody, MA, USA) equipped with the 3D phased array transducer. The US machine, provides an open-source research interface allowing for custom-made applications directly run on the machine, and the 3D transducers. The image resolution for different depth settings will vary from 0.1mm to 0.3mm. In total, we will collect 300 different 3D US scans for each tissue sample (making the total n umber equal to 1500 3D US scans). The collected scans will be enhanced using algorithms developed in Aim1. From the enhanced data, our clinical collaborators will manually identify the needle tips. Three different radiologist, with varying expertise, will be involved during the validation process in order to calculate the inter-user variability error. We will also ask the same users to repeat the needle tip identification process after two weeks to assess the intra-user variability error. The labeled data will be used in order to train the CNN proposed in Aim2. For testing the CNN algorithm, we will collect additional new 500 US scans. The manually identified needle tip locations, from the new dataset, will be compared to the automatically extracted needle tip locations obtained from the algorithms developed in Aims1-2. Euclidean distance error between the two tip locations (manual vs automated) will be calculated for quantitative validation. Clinical data: This study will involve collection of retrospective US data from patients who are enrolled for a liver biopsy or epidural administration as part of their standard of care. Women and minorities will be appropriately represented in the recruited patients. Sex or race will not play a role as an inclusion or exclusion criteria. Specific focus will be given to patients who are 21 years and older and require a liver biopsy or epidural administration. All the US data and the patient information (age, sex, height, weight, and laboratory data) will be assigned a non-identifying alpha-numeric code that will ensure that the risk of re-identification of participants from the acquired data is not possible. Additional information is included in the Protection of Human Subjects. In total, we will collect 1600 different US scans, from 400 patients. For labeling (manual tip and needle shaft localization) in order to train the CNN method developed in Aim2 we will use 1200 scans. During testing, 400 US scans, not part of the training dataset, will be used. Again expert radiologist will be involved during labeling and testing procedures for tip and shaft identification. Error calculations will involve calculating Euclidean distance between the two tip locations (manual vs automated).

Blood Donation Essay Essay

As you are listening to me, you might not think that today is the day that you will save a life. It is quite easy to save a life any day and it only takes a little bit of your time. I’m not talking about being a paramedic or fireman; I am talking about the simple act of donating blood. Almost anybody can donate blood but in order to do so, you must be fit and healthy. In other words; you’re not suffering from a cold, the flu, or any other illnesses. Also, it is extremely critical that you meet the ideal weight which would be anything above 45 KG. You must be between the ages 16-70 if you wish to donate your blood. Make sure that you eat a healthy meal before your donation and that you are drinking an ample amount of liquids preferably juice or water (and absolutely no alcohol) 3 hours prior to donating. [1] There are four key tips in order to have a successful blood donation. Make sure to keep yourself hydrated, wear something comfortable, bring a list of medication that you are taking (as it is important for the doctors to know about any prescription and/or over the counter medications that may be in your system) and lastly, make sure you maintain a healthy level of iron in your diet before donating your blood. Most importantly, you have to relax and feel at ease! Blood donation is an extremely safe procedure and there should be absolutely nothing to be concerned about. [2] Why should you donate blood? The answer is rather quite simple; safe blood saves lives and improves health. Your blood’s main components: plasma, red cells, and platelets are vital for plenty of different uses. Plasma provides the body with plenty of nutrients and protein. Red blood cells are used predominantly in treatments for blood diseases along with cancer. They also help in the making of treating anemia. Platelets contribute to helping repair any signs of damaged body tissue. [3] The donation process from the time you arrive until the time you leave takes about an hour maximum. The donation itself is only about 8-10 minutes on average. The nurse will be sure to cleanse an area on your arm and then insert a sterile needle into it for the blood draw. This shot feels like a  quick pinch and is over in a matter of seconds. Certain donation types such as red cells, platelets or plasma can take up to 2 hours. The nurse draws approximately a pint of blood from you during every donation period. [4] So that now you know how easy it is to donate blood, it’s time to take action. After all, you have plenty of blood, so why not share? When you do, you will feel good about yourself and you will save a life. By giving blood, every donor is contributing to a nation-wide challenge to provide life-saving products whenever and wherever they are needed. Citation: [1] Australian Red Cross Blood Service â€Å"Am I eligible to donate blood?† http://www.donateblood.com.au/who-can-give/am-i-eligible Web. 2014. [2] The American Red Cross â€Å"Donation Process† http://www.redcrossblood.org/donating-blood/tips-successful-donation Web. 2015. [3] â€Å"Why give blood?† http://www.blood.co.uk/giving-blood/why-give-blood/ Web. [4] The American Red Cross â€Å"Donation Process† http://www.redcrossblood.org/donating-blood/donation-process Web. 2015.

Q: Steve Jobs, the Founder of Apple, Was Asked to Come Back as Chief Executive in 1997 When the Business Was Making a Loss. Jobs Was Appointed to Provide a Clearer Vision for the Business and to Improve Its

Many companies throughout the world have suffered from bad leadership decisions or have not adapted well to business cultures brought in by new leaders. This can cause a spread of problems, both internal and external and often the new leader brought in has to make large changes to the way the business is run. The success of this change of leader often depends on their ability to find the shortcomings of the current business structure and to transform it into a competitive force in the future.Steve Jobs founded Apple as a computer company in 1976 and ran it alongside founders Steve Wozniak, Ronald Wayne and investor Mike Markkula. He was a strong minded visionary and often went against other workers ideas. Many rifts were created within apple because of the disagreements he had with other people about the way projects were being run within the company. Eventually, in 1985 Jobs left Apple after being removed as manager of the Mac project, something he had put together and built up.He a cquired Lucasfilm’s animation department Pixar and funded this whilst working on his ‘NeXT’ computer project. He worked at NeXT for a number of years until, in 1995 Apple were convinced by Jobs to buy out his computer company. He then returned to Apple in an informal advisory role at a time when Apple was making the biggest losses since it was founded. In early 1997 after 500 days in the job and over $1 billion in losses the, then CEO was sacked. Jobs agreed to become interim CEO and to take on the responsibility of getting the company back onto the right path.His first move was to dramatically cut the number of products being produced by Apple and focused on a simple matrix structure. He made a laptop for consumer users and a laptop for professional users and the same for desktop computers. This distinctly different structure cut costs and made Apple seem a lot more customer friendly as a company. The next step was looking towards preparing their products for th e future, through development and predictions. The result was a modern line of products that turned around Apple’s fortunes and made them a player in the personal computer market once again.His next focus was creating a media hub, this included the iPod and iTunes and proved extremely successful for Apple and showcased Jobs’ ability to see future trends and lifestyles. Jobs managed to completely transform Apple from a company making giant losses to one of the most valuable companies in the world by stripping it down and completely rebuilding the structure and culture. His critical decision making skills alongside his vision of the future allowed Apple to reconcentrate on innovating and staying ahead of competition.

The Importance Of School Uniforms In Schools - 1693 Words

Approximately 23% of all private and public schools around America have a uniform policy. The idea of bringing uniforms to schools is an issue that has been discussed and argued about for many years. There are very few students who believe that uniforms should be required, and other students just dislike the colors that come with them. Although uniforms have been known to make students look decent, there are many negative side effects that come with them. Some people think that a student wearing a uniform looks well and respectable, but many americans around the world strongly disagree with this statement. However, the popular opinion is clear. American say schools should not implement or enforce school uniforms because, they violate the†¦show more content†¦In the article, â€Å"Do Uniforms Make School Better?†, Mariah Wilde reveals, â€Å" In June of 2007, the United States Supreme Court upheld a lower courts decision affirming a Vermont students right to wear a t- shirt depicting President Bush surrounded by drug and alcohol images. The school had suspended the student . . . The courts however disagreed with the school. . . . They were protected as free political expression† (Wilde). Wilde explains how a student was suspended a t-shirt that was worn that had drugs and alcohol on it, but the courts ruled favor of the student. The supreme court protected the student and said that it was their right to have a political expression. Even though some people like the school in this case disagree with a students opinion does not give them the right to suspend the student. If everyone is entitled to the first Amendment, why are students not? Students are still human beings and they are still allowed to have their freedom of speech and their own opinions. Schools teach us to express ourselves and be our own person, but implementing uniforms takes that right away. To illustrate another reason why uniforms should not be implemented in schools is be cause everyone thinks that uniforms only bring good and no bad, but sadly they are wrong. Uniforms do bring some good, but mainly people are starting to see that uniforms are not getting the right results. Debra Viadero concludes in the article, â€Å"Uniform Effects†, â€Å"DavidShow MoreRelatedThe Importance Of Uniforms In Schools932 Words   |  4 Pagestoday are adapting new uniform policies. Uniforms are essential to a successful school, they bring together different social classes , mitigate bullying, and also maintain a satisfactory reputation and professional look for the associated school. However many schools have not implemented gender neutral uniforms. Many teenagers attending school today have difficulty in expressing themselves due to the fact that the clothes that they desire to wear are unattainable due to school policy. Expressing onesRead MoreThe Importance Of School Uniforms955 Words   |  4 PagesFollowing a school dress code can cause an uncomfortable feeling , can be difficult for families and can decrease individual confidence. Would you like to wear a uniform that your school picked out for you every day and never get to be yourself? Uniforms in education should not be required in the United States unless they want to wear them. Barbara Cruz it might be a solution to help reduce bullying in and out of school (18). Uniforms don’t help students perform better in the classroom, and theyRead MoreImportance Of School Uniforms798 Words   |  4 Pagesto school on time? One way to achieve that is by having schools require their students to wear uniforms during school time. People have formed different opinions regarding uniforms in school. Some support and others oppose them. However, it should go back to the students. Many students in public schools have never tried school uniforms. These students, which include the majority, would not know if it is beneficial to have uniforms or not. Personally, I have been to different ty pes of schools, eachRead MoreThe Importance Of Uniforms In Schools1503 Words   |  7 Pagesâ€Å"More than 60% of schools in America have uniforms† (Dr. Laura Faulk). Although this statement is not true, more and more public schools in America are enforcing the use uniforms. Consequently, schools started requiring uniforms after former President Bill Clinton mentioned the topic in his 1996 State of the Union Speech (Wilde). This action caused an array of emotions because people do not want required clothes in their public schools. Some parents were for the push, however, other parents refusedRead MoreThe Importance Of School Uniforms990 Words   |  4 PagesI will prove that every school should have school uniforms.first off,school uniforms help improve focus.also,the grade point average of most students.lastly,helps stops bullying.Why my debate matters. School uniforms help improve focus.From an expert source â€Å"with no easy way to stand out among the crowd, students might find it worthwhile to do so the hard way by attention to their studies.†First off,without recognizing your friends it is easier to get to class on time and with all that time thinkRead MoreThe Importance Of School Uniforms1014 Words   |  5 Pagesclothing generally does not disrupt education in schools and therefore should have the right to choose their outfits. Students use clothing as an outlet for self-expression and as part of their identity. Advocates for uniforms are convinced that uniforms are effective, however; forcing students to wear uniforms has a negative impact on academic achievement. School uniforms are not beneficial to student’ education in the public school. School uniforms withhold students the opportunity to have creativityRead MoreThe Importance Of Uniforms In Schools813 Words   |  4 PagesStudents from schools with a uniform policy say that uniforms have affected the way they feel about themselves in an unsatisfactory way. Uniforms are proven to slow down the transition into becoming an adult because students are not used to choosing their own clothing. Wearing a uniform opens an opportunity for students to judge each other’s bodies based on how they look and it creates room for drama and bullying. The uniforms can also obstruct a student from expressing themselves. Schools should notRead MoreThe Importance Of School Uniforms1839 Words   |  8 Pagesviews on school uniforms. People feel as if they have to be on either side but are unsure why. One can agree it could be a positive thing or a negative thing or in between it depends on the parents and students. Uniforms are not for everyone but for some it’s perfect. U niforms prevent inappropriate clothing, as far as unfitting logos or gang related colors or attire. Uniforms have been linked to better behavior in schools and in the prevention of distractions in class. However, uniforms violate theRead MoreImportance Of School Uniforms Essay876 Words   |  4 Pagessomething to wear to school the next day? School uniforms are beneficial because first of all, with school uniforms students will fit in with their school and everyone. Second, school uniforms help schools recognize those who do and do not belong on campus. And third, they are cheaper than normal clothes. Some might think that they are boring, but the thing is that school have them in different colors which could make it fun for the students. The first reason why school uniforms are beneficial is becauseRead More The Importance of Uniforms in Public Schools Essay1197 Words   |  5 PagesThe Importance of Uniforms in Public Schools Abstract: For a while, dress codes have been implemented in private and parochial schools across the county. It wasnt until more recent that the issue was brought to discussion about a dress code in public schools. Uniforms serve a purpose to the schools that are adapting the change in attire. The uniform dress code has helped make private and parochial schools more prestigious for their organization and the results of it. Uniforms would be beneficial