The Novel Green Learning Artificial Intelligence for Prostate Cancer Imaging : A Balanced Alternative to Deep Learning and Radiomics - 07/11/23

Doi : 10.1016/j.ucl.2023.08.001

Masatomo Kaneko, MD, PhD ^a,^b,^c, Vasileios Magoulianitis, MS ^d, Lorenzo Storino Ramacciotti, MD ^a,^b, Alex Raman, MS ^e, Divyangi Paralkar, MD ^a,^b, Andrew Chen, MD ^a,^b, Timothy N. Chu, BS ^a,^b, Yijing Yang, MS, PhD ^d, Jintang Xue, MS ^d, Jiaxin Yang, MS ^d, Jinyuan Liu, MS ^d, Donya S. Jadvar ^f, Karanvir Gill, MS, BA ^a,^b, Giovanni E. Cacciamani, MD ^a,^b,^g, Chrysostomos L. Nikias, MS, PhD ^d, Vinay Duddalwar, MD, FRCR ^g, C.-C. Jay Kuo, MS, PhD ^d, Inderbir S. Gill, MD ^a, Andre Luis Abreu, MD ^a,^b,^g,^⁎
^a USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
^b USC Institute of Urology, Center for Image-Guided Surgery, Focal Therapy and Artificial Intelligence for Prostate Cancer
^c Department of Urology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
^d Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, USA
^e Western University of Health Sciences. Pomona, CA, USA
^f Dornsife School of Letters and Science, University of Southern California, Los Angeles, CA, USA
^g Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

^∗Corresponding author. 1441 Eastlake Avenue, Suite 7416, Los Angeles, CA 90089.1441 Eastlake AvenueSuite 7416Los AngelesCA90089

Résumé

The application of artificial intelligence (AI) on prostate magnetic resonance imaging (MRI) has shown promising results. Several AI systems have been developed to automatically analyze prostate MRI for segmentation, cancer detection, and region of interest characterization, thereby assisting clinicians in their decision-making process. Deep learning, the current trend in imaging AI, has limitations including the lack of transparency “black box”, large data processing, and excessive energy consumption. In this narrative review, the authors provide an overview of the recent advances in AI for prostate cancer diagnosis and introduce their next-generation AI model, Green Learning, as a promising solution.

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Keywords : Prostate cancer, Prostate biopsy, Magnetic resonance imaging, Artificial intelligence, Machine learning, Radiomics, Deep learning, Computer vision