The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …

Registration is a core component of many imaging pipelines. In case of clinical scans, with
lower resolution and sometimes substantial motion artifacts, registration can produce poor …

Background Early detection of mild cognitive impairment (MCI), a transitional stage between
normal aging and Alzheimer disease, is crucial for preventing the progression of dementia …

Precision medicine involves answering counterfactual questions such as “Would this patient
respond better to treatment A or treatment B?” These types of questions are causal in nature …

Registration-based methods are commonly used in the automatic segmentation of magnetic
resonance (MR) brain images. However, these methods are not robust to the presence of …

Introduction Normal Pressure Hydrocephalus (NPH) is a prominent type of reversible
dementia that may be treated with shunt surgery, and it is crucial to differentiate it from …

Purpose To develop a fast and fully automated deep learning (DL)–based method for the
MRI planimetric segmentation and measurement of the brainstem and ventricular structures …

BACKGROUND: Machine learning (ML) approaches can significantly improve the classical
R out-based evaluation of the lumbar infusion test (LIT) and the clinical management of the …

Background and Objective: Ventricle volume is closely related to hydrocephalus, brain
atrophy, Alzheimer's, Parkinson's syndrome, and other diseases. To accurately measure the …

Objectives Coronary motion artifacts affect the diagnostic accuracy of coronary CT
angiography (CCTA), especially in the mid right coronary artery (mRCA). The purpose is to …