Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging.

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Title: Handcrafted vs. Deep Radiomics vs. Fusion vs. Deep Learning: A Comprehensive Review of Machine Learning -Based Cancer Outcome Prediction in PET and SPECT Imaging.
Authors: Salmanpour MR; Department of Basic and Translational Research, BC Cancer Research Institute, Vancouver, BC, Canada. msalman@bccrc.ca.; Department of Radiology, University of British Columbia, Vancouver, BC, Canada. msalman@bccrc.ca.; Technological Virtual Collaboration (TECVICO Corp.), Vancouver, BC, Canada. msalman@bccrc.ca., Mehrnia SS; Department of Integrative Oncology, Breast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, Iran., Jabarzadeh Ghandilu S; Technological Virtual Collaboration (TECVICO Corp.), Vancouver, BC, Canada., Safahi Z; Technological Virtual Collaboration (TECVICO Corp.), Vancouver, BC, Canada., Falahati S; Technological Virtual Collaboration (TECVICO Corp.), Vancouver, BC, Canada., Taeb S; Department of Radiology, Guilan University of Medical Sciences, Rasht, Iran., Mousavi G; School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran., Maghsudi M; Technological Virtual Collaboration (TECVICO Corp.), Vancouver, BC, Canada., Shariftabrizi A; Department of Radiology, University of Iowa Carver College of Medicine, Iowa, IA, US., Hacihaliloglu I; Department of Radiology, University of British Columbia, Vancouver, BC, Canada.; Department of Medicine, University of British Columbia, Vancouver, BC, Canada., Rahmim A; Department of Basic and Translational Research, BC Cancer Research Institute, Vancouver, BC, Canada.; Department of Radiology, University of British Columbia, Vancouver, BC, Canada.
Source: Journal of imaging informatics in medicine [J Imaging Inform Med] 2026 Jan 29. Date of Electronic Publication: 2026 Jan 29.
Publication Type: Journal Article; Review
Journal Info: Publisher: Springer Nature Country of Publication: Switzerland NLM ID: 9918663679206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2948-2933 (Electronic) Linking ISSN: 29482925 NLM ISO Abbreviation: J Imaging Inform Med Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2948-2933
DOI:10.1007/s10278-025-01804-z