Litcius/Paper detail

PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation

Vasileios Magoulianitis, Jiaxin Yang, Yijing Yang, Jintang Xue, Masatomo Kaneko, Giovanni Cacciamani, Andre Luis Abreu, Vinay Duddalwar, C.‐C. Jay Kuo, Inderbir S. Gill, C.L. Nikias

2024Computerized Medical Imaging and Graphics11 citationsDOI

Topics & Concepts

InterpretabilityComputer scienceArtificial intelligenceSegmentationDeep learningFeature (linguistics)Pattern recognition (psychology)Pipeline (software)RadiogenomicsMagnetic resonance imagingMachine learningRadiomicsMedicineRadiologyProgramming languageLinguisticsPhilosophyProstate Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical ImagingProstate Cancer Treatment and Research
PCa-RadHop: A transparent and lightweight feed-forward method for clinically significant prostate cancer segmentation | Litcius