Training deep neural networks with noisy clinical labels: toward accurate detection of prostate cancer in US data-Reference-Cited by-同舟云学术

Training deep neural networks with noisy clinical labels: toward accurate detection of prostate cancer in US data

Published:2022-07-26 Issue:9 Volume:17 Page:1697-1705
ISSN:1861-6429
Container-title:International Journal of Computer Assisted Radiology and Surgery
language:en
Short-container-title:Int J CARS

Author:

Javadi Golara^ORCID,Samadi Samareh,Bayat Sharareh,Sojoudi Samira,Hurtado Antonio,Eshumani Walid,Chang Silvia,Black Peter,Mousavi Parvin,Abolmaesumi Purang

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Radiology, Nuclear Medicine and imaging,General Medicine,Surgery,Computer Graphics and Computer-Aided Design,Computer Science Applications,Computer Vision and Pattern Recognition,Biomedical Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11548-022-02707-y.pdf

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3. Shao Y, Wang J, Wodlinger B, Salcudean SE (2020) Improving prostate cancer (PCa) classification performance by using three-player minimax game to reduce data source heterogeneity. IEEE Trans Med Imaging 39:3148–3158

4. Javadi G, Bayat S, Kazemi Esfeh MM, Samadi S, Sedghi A, Sojoudi S, Hurtado A, Chang S, Black P, Mousavi P, Abolmaesumi P (2022) Towards targeted ultrasound-guided prostate biopsy by incorporating model and label uncertainty in cancer detection. Int J Comput Assist Radiol Surg 17:121–128

5. Siddiqui MM, Rais-Bahrami S, Turkbey B, George AK, Rothwax J, Shakir N, Okoro C, Raskolnikov D, Parnes HL, Linehan WM, Merino MJ, Simon RM, Choyke PL, Wood BJ, Pinto PA (2015) Comparison of MR/ultrasound fusion-guided biopsy with ultrasound-guided biopsy for the diagnosis of prostate cancer MR/ultrasound fusion biopsy for prostate cancer MR/ultrasound fusion biopsy for prostate cancer. JAMA 313(4):390–397

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