Landscape of 2D Deep Learning Segmentation Networks Applied to CT Scan from Lung Cancer Patients: A Systematic Review
Somayeh Sadat Mehrnia(Academic Center for Education, Culture and Research), Mohammad R. Salmanpour(University of British Columbia), Yuan Ren(University of British Columbia), Amin Mousavi, Fatemeh Panahandeh, Arman Rahmim(BC Cancer Agency), Arezoo Farmani, Zhino Safahi(University of Kurdistan)
Cited by 12
Related Papers
The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights
|Radiology|2024|210
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge
|Medical Image Analysis|2021|202
Prediction of Cognitive Decline in Parkinson’s Disease Using Clinical and DAT SPECT Imaging Features, and Hybrid Machine Learning Systems
|Diagnostics|2023|88
Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques
|Diagnostics|2023|83
Fusion-based tensor radiomics using reproducible features: Application to survival prediction in head and neck cancer
|Computer Methods and Programs in Biomedicine|2023|78