Advanced Computational Methods for Oncological Image Analysis

• Other Authors: Rundo, Leonardo (Editor), Militello, Carmelo (Editor), Conti, Vincenzo (Editor), Zaccagna, Fulvio (Editor), Han, Changhee (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Subjects: Medicine; melanoma detection; deep learning; transfer learning; ensemble classification; 3D-CNN; immunotherapy; radiomics; self-attention; breast imaging; microwave imaging; image reconstruction; segmentation; unsupervised machine learning; k-means clustering; Kolmogorov-Smirnov hypothesis test; statistical inference; performance metrics; contrast source inversion; brain tumor segmentation; magnetic resonance imaging; survey; brain MRI image; tumor region; skull stripping; region growing; U-Net; BRATS dataset; incoherent imaging; clutter rejection; breast cancer detection; MRgFUS; proton resonance frequency shift; temperature variations; referenceless thermometry; RBF neural networks; interferometric optical fibers; breast cancer; risk assessment; machine learning; texture; mammography; medical imaging; imaging biomarkers; bone scintigraphy; prostate cancer; semisupervised classification; false positives reduction; computer-aided detection; breast mass; mass detection; mass segmentation; Mask R-CNN; dataset partition; brain tumor; classification; shallow machine learning; breast cancer diagnosis; Wisconsin Breast Cancer Dataset; feature selection; dimensionality reduction; principal component analysis; ensemble method; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

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