CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings-Reference-Cited by-同舟云学术

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CT window trainable neural network for improving intracranial hemorrhage detection by combining multiple settings

Published:2020-06 Issue: Volume:106 Page:101850
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Karki Manohar,Cho Junghwan,Lee Eunmi,Hahm Myong-Hun,Yoon Sang-Youl,Kim Myungsoo,Ahn Jae-Yun,Son Jeongwoo,Park Shin-Hyung,Kim Ki-Hong,Park Sinyoul

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference21 articles.

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2. Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: a systematic review of the literature;De Vos;Int J Oral Maxillofac Surg,2009

3. Bone windows for distinguishing malignant from 6benign primary bone tumors on FDG PET/CT;Costelloe;J Cancer,2013

4. The value of “liver windows” settings in the detection of small renal cell carcinomas on unenhanced computed tomography;Sahi;Can Assoc Radiol J,2014

5. CT protocol for acute stroke: tips and tricks for general radiologists;de Lucas;Radiographics,2008

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4. WindowNet: Learnable Windows for Chest X-ray Classification;Journal of Imaging;2023-12-06

5. Comparative Evaluation of Fixed Windowing Strategies on CT Brain Images Using Multiple Deep Learning Models;2023 17th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS);2023-11-08

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