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Deep generative abnormal lesion emphasization validated by nine radiologists and 1000 chest X-rays with lung nodules.
Hanaoka S, Nomura Y, Hayashi N, Sato I, Miki S, Yoshikawa T, Shibata H, Nakao T, Takenaga T, Koyama H, Cho S, Kanemaru N, Fujimoto K, Sakamoto N, Nishiyama T, Matsuzaki H, Yamamichi N, Abe O. Hanaoka S, et al. Among authors: yoshikawa t. PLoS One. 2024 Dec 12;19(12):e0315646. doi: 10.1371/journal.pone.0315646. eCollection 2024. PLoS One. 2024. PMID: 39666722 Free PMC article.
Unsupervised Deep Anomaly Detection in Chest Radiographs.
Nakao T, Hanaoka S, Nomura Y, Murata M, Takenaga T, Miki S, Watadani T, Yoshikawa T, Hayashi N, Abe O. Nakao T, et al. Among authors: yoshikawa t. J Digit Imaging. 2021 Apr;34(2):418-427. doi: 10.1007/s10278-020-00413-2. Epub 2021 Feb 8. J Digit Imaging. 2021. PMID: 33555397 Free PMC article.
Performance changes due to differences among annotating radiologists for training data in computerized lesion detection.
Nomura Y, Hanaoka S, Hayashi N, Yoshikawa T, Koshino S, Sato C, Tatsuta M, Tanaka Y, Kano S, Nakaya M, Inui S, Kusakabe M, Nakao T, Miki S, Watadani T, Nakaoka R, Shimizu A, Abe O. Nomura Y, et al. Among authors: yoshikawa t. Int J Comput Assist Radiol Surg. 2024 Aug;19(8):1527-1536. doi: 10.1007/s11548-024-03136-9. Epub 2024 Apr 16. Int J Comput Assist Radiol Surg. 2024. PMID: 38625446 Free PMC article.
4,778 results