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iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network.

, , , , , , и . CoRR, (2018)

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Maité Colin

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Reproducibility of Training Deep Learning Models for Medical Image Analysis., , , , , , и . MIDL, том 227 из Proceedings of Machine Learning Research, стр. 1269-1287. PMLR, (2023)Automatic detection of spiculation of pulmonary nodules in computed tomography images., , , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 9414 из SPIE Proceedings, стр. 941409. SPIE, (2015)LUNA16 Part 2/2., и . (марта 2019)Towards automatic pulmonary nodule management in lung cancer screening with deep learning., , , , , , , , , и 3 other автор(ы). CoRR, (2016)Surveying the reach and maturity of machine learning and artificial intelligence in astronomy., и . WIREs Data Mining Knowl. Discov., (2020)"Sensie": Probing the sensitivity of neural networks.. J. Open Source Softw., 5 (55): 2180 (2020)Feasibility of end-to-end trainable two-stage U-Net for detection of axillary lymph nodes in contrast-enhanced CT based on sparse annotations., , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 11314 из SPIE Proceedings, SPIE, (2020)Computer-Aided Detection of Ground Glass Nodules in Thoracic CT Images Using Shape, Intensity and Context Features., , , , , и . MICCAI (3), том 6893 из Lecture Notes in Computer Science, стр. 207-214. Springer, (2011)Organ detection in thorax abdomen CT using multi-label convolutional neural networks., , , и . Medical Imaging: Computer-Aided Diagnosis, том 10134 из SPIE Proceedings, стр. 1013416. SPIE, (2017)What happened here? Children integrate physical reasoning to infer actions from indirect evidence., , и . CogSci, cognitivesciencesociety.org, (2021)