Multimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data
(eg, images, texts, or data collected from different sensors), feature engineering (eg …

Recently, deep learning, especially convolutional neural networks, has achieved the
remarkable results in natural image classification and segmentation. At the same time, in the …

Over the past decade, convolutional neural networks (CNN) have shown very competitive
performance in medical image analysis tasks, such as disease classification, tumor …

Automatic segmentation is a fundamental task in computer-assisted medical image analysis.
Convolutional neural networks (CNNs) have been widely used for medical image …

Building general-purpose models that can perceive diverse real-world modalities and solve
various tasks is an appealing target in artificial intelligence. In this paper, we present …

Segmentation of nasopharyngeal carcinoma (NPC) from computed tomography (CT) image
is conducive to the clinical healthcare. Nevertheless, due to the large shape variations …

Nasopharyngeal carcinoma (NPC) is a prevalent and clinically significant malignancy that
predominantly impacts the head and neck area. Precise delineation of the Gross Tumor …

Bearing health condition directly affects the reliability of mechanical equipment. Although
deep learning (DL) algorithms have achieved great results in the field of bearing fault …

Colorectal cancer is one of the malignant tumors with the highest mortality due to the lack of
obvious early symptoms. It is usually in the advanced stage when it is discovered. Thus the …

Abstract Background/Purpose Oropharyngeal cancer (OPC) primary gross tumor volume
(GTVp) segmentation is crucial for radiotherapy. Multiparametric MRI (mpMRI) is …