Multi-modality is widely used in medical imaging, because it can provide multiinformation
about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing …

The U-shaped network is one of the end-to-end convolutional neural networks (CNNs). In
electron microscope segmentation of ISBI challenge 2012, the concise architecture and …

Importance. With the booming growth of artificial intelligence (AI), especially the recent
advancements of deep learning, utilizing advanced deep learning-based methods for …

The accurate segmentation of brain stroke lesions in medical images are critical for early
diagnosis, treatment planning, and monitoring of stroke patients. In recent years, deep …

Deep learning has an enormous impact on medical image analysis. Many computer-aided
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …

This paper provides a comprehensive review of deep learning models for ischemic stroke
lesion segmentation in medical images. Ischemic stroke is a severe neurological disease …

Abstract Treatment selection is becoming increasingly more important in acute ischemic
stroke patient care. Clinical variables and radiological image biomarkers (old age, pre …

Stroke, particularly ischemic stroke, is a major cause of disability and one of the leading
causes of adult mortality worldwide. Early and prompt management of stroke patients can …

Fully convolutional networks have been achieving remarkable results in image semantic
segmentation, while being efficient. Such efficiency results from the capability of segmenting …

Background and objective Acute ischemic stroke (AIS) is a common neurological disorder
characterized by the sudden onset of cerebral ischemia, leading to functional impairments …