Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks-Reference-Cited by-同舟云学术

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Automatic Segmentation of Stroke Lesions in Non-Contrast Computed Tomography Datasets With Convolutional Neural Networks

Published:2020 Issue: Volume:8 Page:94871-94879
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Tuladhar Anup^ORCID,Schimert Serena^ORCID,Rajashekar Deepthi^ORCID,Kniep Helge C.^ORCID,Fiehler Jens^ORCID,Forkert Nils D.^ORCID

Funder

Heart and Stroke Foundation of Canada

T. Chen Fong Fellowship in Medical Imaging Science

Natural Sciences and Engineering Reseasrch Council of Canada (NSERC) Postdoctoral Fellowship

University of Calgary Program for Undergraduate Research Experience (PURE) award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09096283.pdf?arnumber=9096283

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1. Deep learning based 3D multimodal CNN for brain tumor segmentation and detection;Iran Journal of Computer Science;2024-06-16

2. How many specimens make a sufficient training set for automated three-dimensional feature extraction?;Royal Society Open Science;2024-06

3. Hybrid CNN-Transformer Network With Circular Feature Interaction for Acute Ischemic Stroke Lesion Segmentation on Non-Contrast CT Scans;IEEE Transactions on Medical Imaging;2024-06

4. Stroke detection in the brain using MRI and deep learning models;Multimedia Tools and Applications;2024-05-15

5. How many specimens make a sufficient training set for automated 3D feature extraction?;2024-01-12

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