A review of evaluation approaches for explainable AI with applications in cardiology
Explainable artificial intelligence (XAI) elucidates the decision-making process of complex AI
models and is important in building trust in model predictions. XAI explanations themselves …
models and is important in building trust in model predictions. XAI explanations themselves …
Generalizable and explainable deep learning for medical image computing: An overview
Objective This paper presents an overview of generalizable and explainable artificial
intelligence (XAI) in deep learning (DL) for medical imaging, with the aim of addressing the …
intelligence (XAI) in deep learning (DL) for medical imaging, with the aim of addressing the …
Identification and parameter characterization of pores and fractures in shales based on multi-scale digital core data
Y Zhou, X Zhong, X Nie - Advances in Geo-Energy Research, 2024 - ager.yandypress.com
Accurate pore structure characterization, as a basic tool for efficient exploration and
development in reservoirs and digital rock, has become increasingly popular nowadays …
development in reservoirs and digital rock, has become increasingly popular nowadays …
[HTML][HTML] Unsupervised unpaired multiple fusion adaptation aided with self-attention generative adversarial network for scar tissues segmentation framework
Late gadolinium enhancement (LGE) is a specialized imaging technique used in
cardiovascular magnetic resonance (CMR) imaging to detect and characterize areas of scar …
cardiovascular magnetic resonance (CMR) imaging to detect and characterize areas of scar …
Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives
The rapid development of artificial intelligence (AI) has gained importance, with many tools
already entering our daily lives. The medical field of radiation oncology is also subject to this …
already entering our daily lives. The medical field of radiation oncology is also subject to this …
An efficient muscle segmentation method via bayesian fusion of probabilistic shape modeling and deep edge detection
Objective: Paraspinal muscle segmentation and reconstruction from MR images are critical
to implement quantitative assessment of chronic and recurrent low back pains. Due to …
to implement quantitative assessment of chronic and recurrent low back pains. Due to …
Domain generalization for medical image analysis: A survey
Medical Image Analysis (MedIA) has become an essential tool in medicine and healthcare,
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
aiding in disease diagnosis, prognosis, and treatment planning, and recent successes in …
Automated MRI‐based segmentation of intracranial arterial calcification by restricting feature complexity
Purpose To develop an automated deep learning model for MRI‐based segmentation and
detection of intracranial arterial calcification. Methods A novel deep learning model under …
detection of intracranial arterial calcification. Methods A novel deep learning model under …
Cardiac cavity segmentation review in the past decade: Methods and future perspectives
Medical imaging technology has played a vital role in modern medicine and medical care.
Cardiovascular imaging and computing technology are essential for diagnosing and treating …
Cardiovascular imaging and computing technology are essential for diagnosing and treating …
Modelmix: A new model-mixup strategy to minimize vicinal risk across tasks for few-scribble based cardiac segmentation
Pixel-level dense labeling is both resource-intensive and time-consuming, whereas weak
labels such as scribble present a more feasible alternative to full annotations. However …
labels such as scribble present a more feasible alternative to full annotations. However …