LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations-Reference-Cited by-同舟云学术

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations

Published:2024-04-10 Issue:6 Volume:19 Page:1121-1128
ISSN:1861-6429
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

To Minh Nguyen Nhat^ORCID,Fooladgar Fahimeh,Wilson Paul,Harmanani Mohamed,Gilany Mahdi,Sojoudi Samira,Jamzad Amoon,Chang Silvia,Black Peter,Mousavi Parvin,Abolmaesumi Purang

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Institutes of Health Research

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11548-024-03104-3.pdf

Reference25 articles.

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3. Madej A, Wilkosz J, Różański W, Lipiński M (2012) Complication rates after prostate biopsy according to the number of sampled cores. Cent Eur J Urol 65(3):116

4. Feng Y, Yang F, Zhou X, Guo Y, Tang F, Ren F, Guo J, Ji S (2018) A deep learning approach for targeted contrast-enhanced ultrasound based prostate cancer detection. IEEE/ACM Trans Comput Biol Bioinf 16(6):1794–1801

5. Gilany M, Wilson P, Jamzad A, Fooladgar F, To MNN, Wodlinger B, Abolmaesumi P, Mousavi P (2022) Towards confident detection of PCa using high resolution micro-ultrasound. In: Medical image computing and computer assisted interventions, pp 411–420

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