Over the past two decades, machine analysis of medical imaging has advanced rapidly,
opening up significant potential for several important medical applications. As complicated …

As one of the key techniques of artificial intelligence, deep learning has emerged as an
effective approach for analysing medical images. Various imaging techniques including the …

Introduction Bone spinal metastases disrupt the bone homeostasis, inducing a local
imbalance in the bone formation and/or resorption, with consequent loss of the structural …

This paper explores uncertainty quantification (UQ) as an indicator of the trustworthiness of
automated deep-learning (DL) tools in the context of white matter lesion (WML) …

In recent years, Artificial Intelligence (AI) has been widely used in medicine, particularly in
the analysis of medical imaging, which has been driven by advances in computer vision and …

Inspired by the success of Transformers in Computer vision, Transformers have been widely
investigated for medical imaging segmentation. However, most of Transformer architecture …

Automatic classification of bone metastases is a major challenge and is receiving increasing
attention from the research community. One of the major challenges is the accurate …

Objective. Diffusion equation (DE) imaging processing is promising to enhance images
showing lesions of bone metastasis (LBM). The Perona–Malik diffusion (PMD) model, which …

Semi-supervised medical image segmentation (SSMIS) uses consistency learning to
regularize model training, which alleviates the burden of pixel-wise manual annotations …

Rationale and Objectives Metastatic bone tumors significantly reduce patients' quality of life
and expedite cancer spread. Traditional diagnostic methods rely on time-consuming manual …