PPT-Improved Segmentation for Automated Seizure Detection

Author : scarlett | Published Date : 2022-06-18

using Channel Dependent Posteriors Presented By Vinit Shah Neural Engineering Data Consortium Temple University 1 Abstract An important factor of seizure detection

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Improved Segmentation for Automated Seizure Detection: Transcript

using Channel Dependent Posteriors Presented By Vinit Shah Neural Engineering Data Consortium Temple University 1 Abstract An important factor of seizure detection problem known as segmentation defined as the ability to detect start and stop times within a fraction of a second is a challenging and underresearched problem. Ross . Girshick. , Jeff Donahue, Trevor Darrell, . Jitandra. Malik (UC Berkeley). Presenter: . Hossein. . Azizpour. Abstract. Can CNN improve . s.o.a. . object detection results?. Yes, it helps by learning rich representations which can then be combined with computer vision techniques.. Anurag Arnab. Collaborators: . sadeep. . Jayasumana. , . shuai. . zheng. , Philip . torr. Introduction. Semantic Segmentation. Labelling every pixel in an image. A key part of Scene Understanding. Yassine Benajiba. 1. and . Imed. Zitouni. 2. 1 CCLS, Columbia University. 2 IBM T.J. Watson Research Center. ybenajiba@ccls.columbia.edu. , . izitouni@us.ibm.com. . Outline. The Arabic Language. ATB vs. Morph segmentation. CT . SCANS . Neslisah Torosdagli, . Denise K. . Liberton. , . Payal. . Verma. , . Murat . Sincan. ,. . Janice . Lee, . Sumanta. . Pattanaik. , . Ulas. . Bagci. Motivation. The current state-of-art systems lack:. Bharath. . Hariharan. , Pablo . Arbeláez. , . Ross . Girshick. and Jitendra Malik. UC . Berkeley. What is image understanding?. person 1. person 2. horse 1. horse 2. Object Detection. Detect every instance of the category and localize it with a bounding box.. 2015. 2. 12.. Jeany Son. References. Bottom-up Segmentation for Top-down . Detection, CVPR 2013. Segmentation-aware Deformable Part Models, CVPR 2014. 2. Prior Works on Segmentation & Recognition. Friedrich . Müller. , Reiner . Creutzburg. Abstract:. OCT (Optical coherence tomography) has become a popular method for macular degeneration diagnosis. The advantages over other methods are: OCT is . Dan Coughlin. Kevin McCabe. Bob McCarthy. Steve Moffett. Background. Epilepsy is a brain disease that triggers seizures. Electroencephalograms (EEGs) read electrical impulses from the brain. Prediction. Commercially . available seizure detection systems suffer from unacceptably high false alarm rates. . Deep . learning algorithms, like Convolutional Neural Networks (CNNs), have not previously been effective due to the lack of big data resources. . Dierberg KL, Dorjee K, Salvo F, Cronin WA, Boddy J, Cirillo D, et al. Improved Detection of Tuberculosis and Multidrug-Resistant Tuberculosis among Tibetan Refugees, India. Emerg Infect Dis. 2016;22(3):463-468. https://doi.org/10.3201/eid2203.140732. Brittany Davis. Bliss-Moreau Laboratory. MRI as a neuroanatomical tool . in vivo. National Institute of Mental Health Macaque Template: . “NMT v2 Brain” . MRI and Histology Atlases:. Seidlitz et al., 2018. Subset of the publicly available TUH EEG Corpus (. www.isip.piconepress.com/projects/tuh_eeg). .. Evaluation Data:. 50 patients, 239 sessions, 1015 files. 171 hours of data including 16 hours of seizures.. José Ignacio Orlando. 1,2. , Marcos Fracchia. 3. , Valeria . del . Río. 3. and Mariana del Fresno. 2,3,4. 1. . Consejo. Nacional de . Investigaciones. . Científicas. y . Técnicas. , CONICET, Argentina. Laura A. Rice, PhD, MPT, ATP; Alexander . Fliflet. , MS; Mikaela Frechette, MS; Rachel Brokenshire; . Libak. . Abou. ,. MPT, PT; Peter . Presti. , MS; . Harshal. Mahajan, PhD; Jacob . Sosnoff. , PhD; Wendy A. Rogers, PhD.

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