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Deep-learning characterization and quantification of COVID-19 pneumonia lesions from chest CT images.

, , , , , , , , , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 12033 из SPIE Proceedings, SPIE, (2022)

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Julio Peláez Solórzano

Ignacio Mazón Peláez

José Héctor Peláez Valdes

Juan-Carlos Carrillo Peláez

Isaac Bermejo

 

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Emphysema classification using a multi-view convolutional network., , и . ISBI, стр. 519-522. IEEE, (2018)A SR-NET 3D-to-2D Architecture For Paraseptal Emphysema Segmentation., , , , и . ISBI, стр. 303-306. IEEE, (2019)Deep-learning characterization and quantification of COVID-19 pneumonia lesions from chest CT images., , , , , , , , , и 3 other автор(ы). Medical Imaging: Computer-Aided Diagnosis, том 12033 из SPIE Proceedings, SPIE, (2022)Deep learning-based lung segmentation and automatic regional template in chest X-ray images for pediatric tuberculosis., , , , , , и . CoRR, (2023)Deep learning-based lung segmentation and automatic regional template in chest x-ray images for pediatric tuberculosis., , , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 12465 из SPIE Proceedings, SPIE, (2023)Deep-learning strategy for pulmonary artery-vein classification of non-contrast CT images., , , , , и . ISBI, стр. 384-387. IEEE, (2017)A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection., , , и . ISBI, стр. 1-5. IEEE, (2023)Combining collective and artificial intelligence for global health diseases diagnosis using crowdsourced annotated medical images., , , , , , , , , и 1 other автор(ы). EMBC, стр. 3344-3348. IEEE, (2021)