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Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet

Ruiming Cao, Amirhossein Mohammadian Bajgiran, Sohrab Afshari Mirak, Sepideh Shakeri, Xinran Zhong, Dieter Enzmann, Steven Raman, Kyunghyun Sung
2019 IEEE Transactions on Medical Imaging  
We propose a novel multi-class CNN, FocalNet, to jointly detect PCa lesions and predict their aggressiveness using Gleason score (GS).  ...  Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for diagnosing prostate cancer (PCa).  ...  We used FocalNet to jointly detect prostate cancer and predict the fine-grained Gleason score groups.  ... 
doi:10.1109/tmi.2019.2901928 pmid:30835218 fatcat:fidhbaphorfvfe4evabwbc5lny

End-to-end prostate cancer detection in bpMRI via 3D CNNs: effects of attention mechanisms, clinical priori and decoupled false positive reduction

Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman
2021 Medical Image Analysis  
We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model2 for automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR imaging (bpMRI).  ...  Its goal is to accurately identify csPCa lesions from indolent cancer and the wide range of benign pathology that can afflict the prostate gland.  ...  Acknowledgements The authors would like to acknowledge Maarten de Rooij and Ilse Slootweg from Radboud University Medical Center for the annotation of fully delineated masks of prostate cancer for every  ... 
doi:10.1016/j.media.2021.102155 pmid:34245943 fatcat:izmd6e4kdbd55ccjsfa7kpn4w4

End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive Reduction [article]

Anindo Saha, Matin Hosseinzadeh, Henkjan Huisman
2021 arXiv   pre-print
We present a multi-stage 3D computer-aided detection and diagnosis (CAD) model for automated localization of clinically significant prostate cancer (csPCa) in bi-parametric MR imaging (bpMRI).  ...  Its goal is to accurately identify csPCa lesions from indolent cancer and the wide range of benign pathology that can afflict the prostate gland.  ...  Acknowledgements The authors would like to acknowledge Maarten de Rooij and Ilse Slootweg from Radboud University Medical Center for the annotation of fully delineated masks of prostate cancer for every  ... 
arXiv:2101.03244v10 fatcat:l3nmcrhgsjfspjznv6urmotw7a

ProsRegNet: A Deep Learning Framework for Registration of MRI and Histopathology Images of the Prostate [article]

Wei Shao, Linda Banh, Christian A. Kunder, Richard E. Fan, Simon J. C. Soerensen, Jeffrey B. Wang, Nikola C. Teslovich, Nikhil Madhuripan, Anugayathri Jawahar, Pejman Ghanouni, James D. Brooks, Geoffrey A. Sonn (+1 others)
2020 arXiv   pre-print
This important advance will provide radiologists with highly accurate prostate MRI answer keys, thereby facilitating improvements in the detection of prostate cancer on MRI.  ...  This paper presents ProsRegNet, a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer.  ...  Enzmann et al., “Joint prostate cancer detection and gleason score prediction in mp-mri via focalnet,” IEEE Transactions  ... 
arXiv:2012.00991v1 fatcat:3dzgjyd2rray7olkx4xjjn3fgy