Reinforcement learning in medical image analysis: Concepts, applications, challenges, and future directions
Motivation Medical image analysis involves a series of tasks used to assist physicians in
qualitative and quantitative analyses of lesions or anatomical structures which can …
qualitative and quantitative analyses of lesions or anatomical structures which can …
Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model …
A Barragán-Montero, A Bibal… - Physics in Medicine …, 2022 - iopscience.iop.org
The interest in machine learning (ML) has grown tremendously in recent years, partly due to
the performance leap that occurred with new techniques of deep learning, convolutional …
the performance leap that occurred with new techniques of deep learning, convolutional …
[HTML][HTML] A review of deep learning-based three-dimensional medical image registration methods
Medical image registration is a vital component of many medical procedures, such as image-
guided radiotherapy (IGRT), as it allows for more accurate dose-delivery and better …
guided radiotherapy (IGRT), as it allows for more accurate dose-delivery and better …
Deep learning for medical image registration: A comprehensive review
Image registration is a critical component in the applications of various medical image
analyses. In recent years, there has been a tremendous surge in the development of deep …
analyses. In recent years, there has been a tremendous surge in the development of deep …
[HTML][HTML] Medical image registration via neural fields
Image registration is an essential step in many medical image analysis tasks. Traditional
methods for image registration are primarily optimization-driven, finding the optimal …
methods for image registration are primarily optimization-driven, finding the optimal …
A review on AI-based medical image computing in head and neck surgery
Head and neck surgery is a fine surgical procedure with a complex anatomical space,
difficult operation and high risk. Medical image computing (MIC) that enables accurate and …
difficult operation and high risk. Medical image computing (MIC) that enables accurate and …
Multi-scale neural odes for 3d medical image registration
Image registration plays an important role in medical image analysis. Conventional
optimization based methods provide an accurate estimation due to the iterative process at …
optimization based methods provide an accurate estimation due to the iterative process at …
Deep reinforcement learning for image-to-image translation
Most existing Image-to-Image Translation (I2IT) methods generate images in a single run of
a deep learning (DL) model. However, designing such a single-step model is always …
a deep learning (DL) model. However, designing such a single-step model is always …
Diffeomorphic image registration with neural velocity field
Diffeomorphic image registration, offering smooth transformation and topology preservation,
is required in many medical image analysis tasks. Traditional methods impose certain …
is required in many medical image analysis tasks. Traditional methods impose certain …
Heuristic multi-modal integration framework for liver tumor detection from multi-modal non-enhanced MRIs
The detection of liver tumors from non-enhanced Magnetic Resonance Imaging (MRI) has
become crucial for current diagnosis and treatment due to the avoidance of contrast-agent …
become crucial for current diagnosis and treatment due to the avoidance of contrast-agent …