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Asymmetric Loss Functions and Deep Densely Connected Networks for Highly Imbalanced Medical Image Segmentation: Application to Multiple Sclerosis Lesion Detection [article]

Seyed Raein Hashemi, Seyed Sadegh Mohseni Salehi, Deniz Erdogmus, Sanjay P. Prabhu, Simon K. Warfield, Ali Gholipour
2018 IEEE Access   accepted
Fully convolutional deep neural networks have been asserted to be fast and precise frameworks with great potential in image segmentation.  ...  One of the major challenges in training such networks raises when data is unbalanced, which is common in many medical imaging applications such as lesion segmentation where lesion class voxels are often  ...  CONCLUSION To effectively train deep neural networks for highly unbalanced lesion segmentation in medical imaging, we added asymmetric loss layer to two state-of-the-art 3D fully convolutional deep neural  ... 
doi:10.1109/access.2018.2886371 pmid:31528523 pmcid:PMC6746414 arXiv:1803.11078v4 fatcat:i4ctg3fnrvgabjjwmxxqfpfcfm

Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI [article]

Jinyoung Kim, Remi Patriat, Jordan Kaplan, Oren Solomon, Noam Harel
2020 arXiv   pre-print
During the end-to-end training, label probabilities of dentate and interposed nuclei are independently learned with a hybrid loss, handling highly imbalanced data.  ...  It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of the cerebellum system and its utility in deep brain stimulation treatment.  ...  Acknowledgements This work was supported in part by R01-NS081118, R01-NS113746, P50-NS098573, P30-NS076408 and P41-EB027061.  ... 
arXiv:2004.09788v3 fatcat:io34ocviqnfq7eeudkjxdyefgy

Deep Cerebellar Nuclei Segmentation via Semi-Supervised Deep Context-Aware Learning from 7T Diffusion MRI

Jinyoung Kim, Remi Patriat, Jordan Kaplan, Oren Solomon, Noam Harel
2020 IEEE Access  
During the end-to-end training, label probabilities of dentate and interposed nuclei are independently learned with a hybrid loss, handling highly imbalanced data.  ...  It is thus a crucial step to accurately segment deep cerebellar nuclei for the understanding of the cerebellum system and its utility in deep brain stimulation treatment.  ...  Furthermore, other similarity loss functions are introduced for detecting multiple sclerosis lesion in highly imbalanced data [38] and reducing the Hausdorff Distance in segmentation [39] .  ... 
doi:10.1109/access.2020.2998537 pmid:32656051 pmcid:PMC7351101 fatcat:ihkyozka7vbhvk7gxa4qkohxqy

Review of Machine Learning Applications Using Retinal Fundus Images

Yeonwoo Jeong, Yu-Jin Hong, Jae-Ho Han
2022 Diagnostics  
With the feasibility and development of deep learning methods, machines are now able to interpret complex features in medical data, which leads to rapid advancements in automation.  ...  Automating screening and diagnosis in the medical field saves time and reduces the chances of misdiagnosis while saving on labor and cost for physicians.  ...  The machine learning applications for images in the medical field include lesion detection, automatic diagnosis, medical image segmentation, and medical image generation.  ... 
doi:10.3390/diagnostics12010134 pmid:35054301 pmcid:PMC8774893 fatcat:oefecnzbsnglzkufstzq37epv4

A review of uncertainty quantification in deep learning: Techniques, applications and challenges

Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U. Rajendra Acharya, Vladimir Makarenkov, Saeid Nahavandi
2021 Information Fusion  
(e.g., image restoration), medical image analysis (e.g., medical image classification and segmentation), natural language processing (e.g., text classification, social media texts and recidivism risk-scoring  ...  In this regard, researchers have proposed different UQ methods and examined their performance in a variety of applications such as computer vision (e.g., selfdriving cars and object detection), image processing  ...  Acknowledgment This work was partially supported by the Australian Research Council's Discovery Projects funding scheme (project DP190102181) and the Natural Sciences and Engineering Research Council of  ... 
doi:10.1016/j.inffus.2021.05.008 fatcat:yschhguyxbfntftj6jv4dgywxm

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
; Skocaj, Danijel 1532 End-To-End Training of a Two-Stage Neural Network for Defect Detection GAP: Quantifying the Generative Adversarial Set and Class Feature Applicability of Deep Neural Networks Deep  ...  Contextual Atrous Residual Network for Brain Tumor Detection & Segmentation DAY 1 -Jan 12, 2021 Le, Ngan; Le, Trung; Bui, Duc Toan; Luu, Khoa; Savvides, Marios 1688 Offset Curves Loss for Imbalanced  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

ECR 2015 Book of Abstracts - A - Postgraduate Educational Programme

2015 Insights into Imaging  
The first solution requires the user to be constantly connected to the network, whilst the second solution can continue to function after disconnecting from the network.  ...  To learn about the brain's activity and its connections. The clinical success of PET/CT in oncological imaging has opened opportunities for applications in cardiology.  ...  BSGI is a cost-effective, highly sensitive and specific technique focused primarily on detection of tumours, especially in women with dense breasts.  ... 
doi:10.1007/s13244-015-0386-0 pmid:25708993 pmcid:PMC4349897 fatcat:m7eyvqcwojfpvf3lr5hy6dwjb4

ECR 2016 Book of Abstracts - A - Postgraduate Educational Programme

2016 Insights into Imaging  
The first solution requires the user to be constantly connected to the network, whilst the second solution can continue to function after disconnecting from the network.  ...  To learn about the brain's activity and its connections. The clinical success of PET/CT in oncological imaging has opened opportunities for applications in cardiology.  ...  BSGI is a cost-effective, highly sensitive and specific technique focused primarily on detection of tumours, especially in women with dense breasts.  ... 
doi:10.1007/s13244-016-0474-9 pmid:26873353 pmcid:PMC4762839 fatcat:itxslbcacjhh3kixfkcwmdbt44

ECR 2011 Book of Abstracts - A - Postgraduate Educational Programme

2011 Insights into Imaging  
The first solution requires the user to be constantly connected to the network, whilst the second solution can continue to function after disconnecting from the network.  ...  To learn about the brain's activity and its connections. The clinical success of PET/CT in oncological imaging has opened opportunities for applications in cardiology.  ...  BSGI is a cost-effective, highly sensitive and specific technique focused primarily on detection of tumours, especially in women with dense breasts.  ... 
doi:10.1007/s13244-011-0078-3 pmid:23100070 pmcid:PMC3533621 fatcat:qa3ln4hhvve2hhumgwwnmykgoe

ECR 2013 Book of Abstracts - A - Postgraduate Educational Programme

2013 Insights into Imaging  
The first solution requires the user to be constantly connected to the network, whilst the second solution can continue to function after disconnecting from the network.  ...  To learn about the brain's activity and its connections. The clinical success of PET/CT in oncological imaging has opened opportunities for applications in cardiology.  ...  BSGI is a cost-effective, highly sensitive and specific technique focused primarily on detection of tumours, especially in women with dense breasts.  ... 
doi:10.1007/s13244-013-0227-y pmid:23468009 pmcid:PMC3666656 fatcat:yitsk227mba2pl7wcypouf6tz4

Development and Visual Assessment of a Multi-Modality Brain Segmentation Pipeline

Caroline Magg, Renata Georgia Raidou
2021
Second, we design and implement an interactive web-based VA application for the assessment of algorithm performance and results.  ...  However, current VA applications are limited and do not provide flexible comparison capabilities that are able to drill down from large cohorts of patients into individual image slices.  ...  Arnold, and T. Arbel. Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation. Medical Image Analysis, 59:101557, 2020. [98] V.  ... 
doi:10.34726/hss.2021.92822 fatcat:nh7eyl57rfh7npolqijoiwacei

Panel and Study Groups

2013 Neuropsychopharmacology  
Each brain has been genotyped with 650K to 1 million SNP chips from Illumina and screened for neuropathology, toxicology and high quality RNA.  ...  to both schizophrenia and affective disorders (po.05).  ...  TLS' first repositioning candidate is lisinopril as a potential treatment for multiple sclerosis.  ... 
doi:10.1038/npp.2013.278 fatcat:expu2u3f3reypazj7tt7jhybfa

A Review of JACC Journal Articles on the Topic of Interventional Cardiology: 2011–2012

2013 Journal of the American College of Cardiology  
Adjusted hazard ratios for 1-year death were 1.39 (95% confidence interval [CI]: 1.01 to 1.89) for procedural MI and 5.37 (95% CI: 3.90 to 7.38) for spontaneous MI.  ...  (Early Glycoprotein IIb/IIIa Inhibition in Non-ST-Segment Elevation Acute Coronary Syndrome) study and the SYNERGY (Superior Yield of the New strategy of Enoxaparin, Revascularization and GlYcoprotein  ...  The changes in dense calcium need to be interpreted with caution since the polymeric struts are detected as "pseudo" dense calcium structures with the VH-IVUS imaging modality.  ... 
doi:10.1016/j.jacc.2013.09.004 fatcat:jysqnvm36ba5zeym6vg56ipcu4

Supplementum 222: Joint annual meeting Swiss Society of Paediatrics and the Swiss Society for Allergology and Immunology, jointly organized with the 4th Lymphoid Tissue Meeting "Focus on Stromal Cells"

2017 Swiss Medical Weekly  
Therefore, to date, FRCs were primarily thought to negatively regulate the functions of newly activated T cells.  ...  We investigated the ability of human LNSCs derived from RA, RA-risk and healthy individuals to sense and respond to pathogens.  ...  used for the treatment of relapsing forms of multiple sclerosis (MS).  ... 
doi:10.4414/smw.2017.20424 pmid:33379860 fatcat:bpqm632nhffkjhzwtlemyopusa

SIREV Congress Abstracts Murcia (Spain), June 24-26, 2021

2021 Ophthalmic Research  
functions, although they may also contribute to image formation.  ...  Revision of digitised medical history and analysis of multimodal image of spectral domain OCT.  ...  The main objective of this study was to evaluate the loss-of-function (LoF) effect of this candidate gene in zebrafish.  ... 
doi:10.1159/000517823 pmid:34157711 fatcat:rvvpiptuobg5blfgjdomm6vyyu
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