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

Key Points

• Machine learning applications in PET and SPECT imaging improve cancer outcome predictions significantly.
• The review evaluates various methodologies, including handcrafted and deep learning approaches, indicating their respective efficiencies.
• Analysis provides insights on deep radiomics and fusion techniques, emphasizing advancements in cancer diagnostics.
• Findings suggest the integration of these methods may enhance prognosis accuracy, yet further exploration is needed for clinical validation.