Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
[HTML][HTML] Paradigm shift from Artificial Neural Networks (ANNs) to deep Convolutional Neural Networks (DCNNs) in the field of medical image processing
Images and other types of unstructural data in the medical domain are rapidly becoming
data-intensive. Actionable insights from these complex data present new opportunities but …
data-intensive. Actionable insights from these complex data present new opportunities but …
Synthesis of pediatric brain tumor images with mass effect
In children, brain tumors are the leading cause of cancer-related death. The amount of
labeled data in children is much lower than that for adult subjects. This paper proposes a …
labeled data in children is much lower than that for adult subjects. This paper proposes a …
Geometric deep learning for medical image processing problems
F Sinzinger - 2024 - openarchive.ki.se
Medical image processing provides an expanding set of methods and applications to
improve clinical diagnosis, decision-making, and treatment planning through specific …
improve clinical diagnosis, decision-making, and treatment planning through specific …
[图书][B] Advanced machine learning methods for oncological image analysis
M Astaraki - 2022 - search.proquest.com
Cancer is a major public health problem, accounting for an estimated 10 million deaths
worldwide in 2020 alone. Rapid advances in the field of image acquisition and hardware …
worldwide in 2020 alone. Rapid advances in the field of image acquisition and hardware …