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Towards Robust and Accurate Detection of Abnormalities in Musculoskeletal Radiographs with a Multi-Network Model

Shuang Liang, Yu Gu
<span title="2020-06-02">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
of musculoskeletal abnormalities via musculoskeletal radiographs.  ...  , and Kappa score) using the MURA dataset (a large dataset of bone X-rays).  ...  The abnormalities-detection-level of the proposed model is also not worse than that of radiologists.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20113153">doi:10.3390/s20113153</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32498374">pmid:32498374</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fae6n546hjbrpmjdeavgw3ea2y">fatcat:fae6n546hjbrpmjdeavgw3ea2y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201106222054/https://res.mdpi.com/d_attachment/sensors/sensors-20-03153/article_deploy/sensors-20-03153.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/59/7c/597c9896a41bbbff699b7ff82e7bf77b1e5e6426.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s20113153"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Medical Datasets Collections for Artificial Intelligence-based Medical Image Analysis [article]

Yang Wen
<span title="2021-02-18">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The images of these datasets are captured by different cameras, thus vary from each other in modality, frame size and capacity.  ...  For data accessibility, we also provide the websites of most datasets and hope this will help the readers reach the datasets.  ...  The dataset is available at https://luna16.grand-challenge.org/Data/ MURA [30] MURA (musculoskeletal radiographs) is a large dataset of bone X-rays.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2102.01549v3">arXiv:2102.01549v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4vj7uh7b45b7rcsxqb2hptvehi">fatcat:4vj7uh7b45b7rcsxqb2hptvehi</a> </span>
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A calibrated deep learning ensemble for abnormality detection in musculoskeletal radiographs

Minliang He, Xuming Wang, Yijun Zhao
<span title="2021-04-27">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
In our study, we introduce a new calibrated ensemble of deep learners for the task of identifying abnormal musculoskeletal radiographs.  ...  abnormalities in musculoskeletal X-rays.  ...  Discussion In this study, we evaluated five deep learning approaches for the task of detecting abnormalities using musculoskeletal radiographs.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41598-021-88578-w">doi:10.1038/s41598-021-88578-w</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33907257">pmid:33907257</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mpzesw4jeff7tasdzgxda6yksa">fatcat:mpzesw4jeff7tasdzgxda6yksa</a> </span>
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Towards to Reasonable Decision Basis in Automatic Bone X-Ray Image Classification: A Weakly-Supervised Approach

Jianjie Lu, Kai-yu Tong
<span title="2019-07-17">2019</span> <i title="Association for the Advancement of Artificial Intelligence (AAAI)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wtjcymhabjantmdtuptkk62mlq" style="color: black;">PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE</a> </i> &nbsp;
We test the proposed method on a bone X-ray dataset. Results show that it achieves significant improvements in lesion location.  ...  A weakly-supervised framework is proposed that cannot only make class inference but also provides reasonable decision basis in bone X-ray images.  ...  MURA Dataset: Towards Radiologist-level Abnormality Detection in Musculoskeletal Radiographs. In International Conference on Medical Imaging with Deep Learning.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1609/aaai.v33i01.33019985">doi:10.1609/aaai.v33i01.33019985</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2qzhqekilvfdll4nyz2xzso2qm">fatcat:2qzhqekilvfdll4nyz2xzso2qm</a> </span>
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Self-Taught Semi-Supervised Anomaly Detection on Upper Limb X-rays [article]

Antoine Spahr, Behzad Bozorgtabar, Jean-Philippe Thiran
<span title="2021-02-22">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Detecting anomalies in musculoskeletal radiographs is of paramount importance for large-scale screening in the radiology workflow.  ...  Through extensive experiments, we show that our method outperforms baselines across unsupervised and self-supervised anomaly detection settings on a real-world medical dataset, the MURA dataset.  ...  EXPERIMENTAL RESULTS Dataset and Preprocessing We evaluate the proposed method on the Stanford Musculoskeletal Radiograph (MURA) dataset [5] composed of around 40,000 upper limb X-ray scans annotated  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2102.09895v2">arXiv:2102.09895v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nzf4mmcqyrcutafxr4jhtobalu">fatcat:nzf4mmcqyrcutafxr4jhtobalu</a> </span>
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Arthritis Detection using AI

Suneetha J, Prasanjit Singh, Krishmal Shrestha, Abhijeet Singh, Pallavi Bhagat
<span title="2021-09-15">2021</span> <i title="Zenodo"> Zenodo </i> &nbsp;
In the medical field, AI could be applied in a variety of fields, including cancer detection, tumours, and heart disease. Arthritis is another medical condition where AI can be helpful.  ...  As a result, we employed AI (Deep Learning) to detect Arthritis at an earlier stage with more accuracy.  ...  Data Sets MURA (Musculoskeletal Radio Graphs) is a comprehensive collection of X-rays of Recent Trends in Information Technology and its Application Volume 4 Issue 3 the bones.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.5508684">doi:10.5281/zenodo.5508684</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/b67xczukx5asphigmjl5e7g6ly">fatcat:b67xczukx5asphigmjl5e7g6ly</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210919061613/https://zenodo.org/record/5508685/files/Arthritis%20Detection%20Using%20AI%20-Formatted%20Paper.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/14/e2/14e2c57e989c9aa73553e5d57ed6d4c171bb798c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.5508684"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>

X-Ray Bone Fracture Classification Using Deep Learning: A Baseline for Designing a Reliable Approach

Leonardo Tanzi, Enrico Vezzetti, Rodrigo Moreno, Sandro Moos
<span title="2020-02-22">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
In recent years, bone fracture detection and classification has been a widely discussed topic and many researchers have proposed different methods to tackle this problem.  ...  Each study is summarized and evaluated using a radar graph with six values: area under the curve (AUC), test accuracy, sensitivity, specificity, dataset size and labelling reliability.  ...  MURA: Large Dataset for Abnormality Detection in Musculoskeletal Radiographs This subsection focuses on the work of Rajpurkar et al. [26] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10041507">doi:10.3390/app10041507</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ic25ln5konhzxdfz6l4yqfgbjq">fatcat:ic25ln5konhzxdfz6l4yqfgbjq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200227192047/https://res.mdpi.com/d_attachment/applsci/applsci-10-01507/article_deploy/applsci-10-01507-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/99/ab/99abc31462afed3f6e35a51e0106dd6b90075ff8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app10041507"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Predictive and discriminative localization of pathology using high resolution class activation maps with CNNs

Sumeet Shinde, Priyanka Tupe-Waghmare, Tanay Chougule, Jitender Saini, Madhura Ingalhalikar
<span title="2021-07-14">2021</span> <i title="PeerJ"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zs2czkfyybggbpvr26rbyxpsjy" style="color: black;">PeerJ Computer Science</a> </i> &nbsp;
(ISIC open dataset—25,331 cases) and (2) predicting bone fractures (MURA open dataset—40,561 images) (3) predicting Parkinson's disease (PD) from neuromelanin sensitive MRI (small cohort-80 subjects).  ...  Consequently these provide a coarse localization that may not be able to capture subtle abnormalities in medical images.  ...  MURA MURA (musculoskeletal radiographs) is one of the largest public radiographic image datasets collected from HIPAA-compliant images from the Picture Archive and Communication System (PACS) of Stanford  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7717/peerj-cs.622">doi:10.7717/peerj-cs.622</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34322593">pmid:34322593</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8293926/">pmcid:PMC8293926</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ppgz7dhk6bdqhptwtftmcm4a3i">fatcat:ppgz7dhk6bdqhptwtftmcm4a3i</a> </span>
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Learn2Agree: Fitting with Multiple Annotators without Objective Ground Truth [article]

Chongyang Wang, Yuan Gao, Chenyou Fan, Junjie Hu, Tin Lun Lam, Nicholas D. Lane, Nadia Bianchi-Berthouze
<span title="2022-05-25">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
., the rehabilitation for some chronic diseases, and the prescreening of some musculoskeletal abnormalities without further medical examinations.  ...  The proposed method can be easily added to existing backbones, with experiments on two medical datasets showed better agreement levels with annotators.  ...  is achieved on the MURA dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.03596v2">arXiv:2109.03596v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/shxljxcngfhxvc4gbe7ycutwte">fatcat:shxljxcngfhxvc4gbe7ycutwte</a> </span>
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A Survey of Methods and Technologies Used for Diagnosis of Scoliosis

Ilona Karpiel, Adam Ziębiński, Marek Kluszczyński, Daniel Feige
<span title="2021-12-16">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis in the form of a brief review. This article aims to point out the advantages of select methods.  ...  Towards Automatic Report Generation in Spine Radiology Using Weakly Supervised Framework.  ...  for research towards artificial intelligence and scoliosis diagnosis.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21248410">doi:10.3390/s21248410</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34960509">pmid:34960509</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8707023/">pmcid:PMC8707023</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/m3p7dai57ncqfdxt3eydfmnlay">fatcat:m3p7dai57ncqfdxt3eydfmnlay</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211218024221/https://mdpi-res.com/d_attachment/sensors/sensors-21-08410/article_deploy/sensors-21-08410.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bb/96/bb967ee6fa3d9f730cd99d30b8bb3900495330f5.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21248410"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8707023" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Artificial Intelligence Surgery: How Do We Get to Autonomous Actions in Surgery?

Andrew A. Gumbs, Isabella Frigerio, Gaya Spolverato, Roland Croner, Alfredo Illanes, Elie Chouillard, Eyad Elyan
<span title="2021-08-17">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
Fortuitously, as the field of robotics in surgery has improved, more surgeons are becoming interested in technology and the potential of autonomous actions in procedures such as interventional radiology  ...  Ultimately, there may be a paradigm shift that needs to occur in the surgical community as more surgeons with expertise in AI may be needed to fully unlock the potential of AIS in a safe, efficacious and  ...  Examples include datasets related to musculoskeletal radiographs such as MURA [64] , which contains 40,561 images from 14,863 studies representing 11,184 different patients.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21165526">doi:10.3390/s21165526</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34450976">pmid:34450976</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8400539/">pmcid:PMC8400539</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/xrghczfytvahzkmup5vmf6eb3a">fatcat:xrghczfytvahzkmup5vmf6eb3a</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210820102200/https://res.mdpi.com/d_attachment/sensors/sensors-21-05526/article_deploy/sensors-21-05526-v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c8/a6/c8a6a56d226f56b04bf5d5257f94e8295fbafbd8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s21165526"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8400539" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions [article]

Fouzia Altaf, Syed M. S. Islam, Naveed Akhtar, Naeem K. Janjua
<span title="2019-02-15">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
This enables us to single out 'lack of appropriately annotated large-scale datasets' as the core challenge (among other challenges) in this research direction.  ...  This technology has recently attracted so much interest of the Medical Imaging community that it led to a specialized conference in 'Medical Imaging with Deep Learning' in the year 2018.  ...  Rajpurkar et al. [111] recently released a data set MURA which consists of 40,561 images from 14,863 musculoskeletal studies labeled by radiologists as either normal or abnormal.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.05655v1">arXiv:1902.05655v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mjplenjrprgavmy5ssniji4cam">fatcat:mjplenjrprgavmy5ssniji4cam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200917223338/https://arxiv.org/pdf/1902.05655v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5f/35/5f35562b066d6c7e60d4f847a477f8dfee0998c1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1902.05655v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks [article]

Zhifei Zhang, Wanling Gao, Fan Zhang, Yunyou Huang, Shaopeng Dai, Fanda Fan, Jianfeng Zhan, Mengjia Du, Silin Yin, Longxin Xiong, Juan Du, Yumei Cheng, Xiexuan Zhou, Rui Ren (+2 others)
<span title="2019-01-03">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, a group of life scientists, clinicians, computer scientists and engineers sit together to discuss several fundamental issues.  ...  Fifth, what are the performance gaps of state-of-the-practice and state-of-the-art systems handling big medical data currently or in future?  ...  MURA [174] is a benchmark database of musculoskeletal radiographs containing 40,561 multi-view radiographic images collected from 12,173 patients, with a total of 14,863 studies covering seven study  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1901.00642v1">arXiv:1901.00642v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fak46q7bgzesll6y4h7i6mcysi">fatcat:fak46q7bgzesll6y4h7i6mcysi</a> </span>
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Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions

Fouzia Altaf, Syed M S Islam, Naveed Akhtar, Naeem Khalid Janjua
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
This technology has recently attracted so much interest of the Medical Imaging Community that it led to a specialized conference in "Medical Imaging with Deep Learning" in the year 2018.  ...  This paper does not assume prior knowledge of deep learning and makes a significant contribution in explaining the core deep learning concepts to the non-experts in the Medical Community.  ...  [116] recently released a data set MURA which consists of 40,561 images from 14,863 musculoskeletal studies labeled by radiologists as either normal or abnormal.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2929365">doi:10.1109/access.2019.2929365</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/arimcbjaxrd3zcsjyzd7abjgd4">fatcat:arimcbjaxrd3zcsjyzd7abjgd4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429005944/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08764525.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1e/56/1e56c088874e827802e02a606a1ecdab06e0e754.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2929365"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

An overview of deep learning in medical imaging focusing on MRI

Alexander Selvikvåg Lundervold, Arvid Lundervold
<span title="">2018</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6xf7xkljbve5nldkiakg3lwhc4" style="color: black;">Zeitschrift für Medizinische Physik</a> </i> &nbsp;
We provide a short overview of recent advances and some associated challenges in machine learning applied to medical image processing and image analysis.  ...  These developments have a huge potential for medical imaging technology, medical data analysis, medical diagnostics and healthcare in general, slowly being realized.  ...  Determine whether a bone X-ray is normal or abnormal https://stanfordmlgroup.github.io/competitions/mura/ the basic building blocks described above, placed according to the ideas behind, say, ResNet and  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.zemedi.2018.11.002">doi:10.1016/j.zemedi.2018.11.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kkimovnwcrhmth7mg6h6cpomjm">fatcat:kkimovnwcrhmth7mg6h6cpomjm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428190559/https://hvlopen.brage.unit.no/hvlopen-xmlui/bitstream/handle/11250/2578841/Lundervold.pdf?sequence=4" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0b/b1/0bb10d36ebdded9d9f927b70ffa7594a7542b604.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.zemedi.2018.11.002"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>
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