Deep reinforcement learning in computer vision: a comprehensive survey
Deep reinforcement learning augments the reinforcement learning framework and utilizes
the powerful representation of deep neural networks. Recent works have demonstrated the …
the powerful representation of deep neural networks. Recent works have demonstrated the …
Estimating medical image registration error and confidence: A taxonomy and scoping review
J Bierbrier, HE Gueziri, DL Collins - Medical Image Analysis, 2022 - Elsevier
Given that image registration is a fundamental and ubiquitous task in both clinical and
research domains of the medical field, errors in registration can have serious consequences …
research domains of the medical field, errors in registration can have serious consequences …
A survey on deep learning in medical image registration: New technologies, uncertainty, evaluation metrics, and beyond
Over the past decade, deep learning technologies have greatly advanced the field of
medical image registration. The initial developments, such as ResNet-based and U-Net …
medical image registration. The initial developments, such as ResNet-based and U-Net …
Uncertainty‐aware Visualization in Medical Imaging‐A Survey
C Gillmann, D Saur, T Wischgoll… - Computer Graphics …, 2021 - Wiley Online Library
Medical imaging (image acquisition, image transformation, and image visualization) is a
standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students …
standard tool for clinicians in order to make diagnoses, plan surgeries, or educate students …
Deformable image registration by combining uncertainty estimates from supervoxel belief propagation
MP Heinrich, IJA Simpson, BŁW Papież, M Brady… - Medical image …, 2016 - Elsevier
Discrete optimisation strategies have a number of advantages over their continuous
counterparts for deformable registration of medical images. For example: it is not necessary …
counterparts for deformable registration of medical images. For example: it is not necessary …
Machine learning in medical imaging
Medical imaging is an indispensable component of modern healthcare, playing a critical role
in diagnosis, staging, and the assessment of treatment response for most major medical …
in diagnosis, staging, and the assessment of treatment response for most major medical …
Hierarchical prediction of registration misalignment using a convolutional LSTM: Application to chest CT scans
In this paper we propose a supervised method to predict registration misalignment using
convolutional neural networks (CNNs). This task is casted to a classification problem with …
convolutional neural networks (CNNs). This task is casted to a classification problem with …
Quantitative error prediction of medical image registration using regression forests
Predicting registration error can be useful for evaluation of registration procedures, which is
important for the adoption of registration techniques in the clinic. In addition, quantitative …
important for the adoption of registration techniques in the clinic. In addition, quantitative …
FocalErrorNet: Uncertainty-aware focal modulation network for inter-modal registration error estimation in ultrasound-guided neurosurgery
In brain tumor resection, accurate removal of cancerous tissues while preserving eloquent
regions is crucial to the safety and outcomes of the treatment. However, intra-operative …
regions is crucial to the safety and outcomes of the treatment. However, intra-operative …
Accuracy estimation for medical image registration using regression forests
This paper reports a new automatic algorithm to estimate the misregistration in a quantitative
manner. A random regression forest is constructed, predicting the local registration error …
manner. A random regression forest is constructed, predicting the local registration error …