Abstract 3D MRI Brain Tumor Segmentation is of great significance in clinical diagnosis and
treatment. Accurate segmentation results are critical for localization and spatial distribution …

Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Brain tumor segmentation (BTS) in magnetic resonance image (MRI) is crucial for brain
tumor diagnosis, cancer management and research purposes. With the great success of the …

The accurate prediction of isocitrate dehydrogenase (IDH) mutation and glioma
segmentation are important tasks for computer-aided diagnosis using preoperative …

Accurate volumetric segmentation of brain tumors and tissues is beneficial for quantitative
brain analysis and brain disease identification in multi-modal Magnetic Resonance (MR) …

Brain tumors are highly hazardous, and precise automated segmentation of brain tumor
subregions has great importance and research significance on the diagnosis and treatment …

Background and objective Retinal vessel segmentation plays an important role in the
automatic retinal disease screening and diagnosis. How to segment thin vessels and …

Accurate segmentation of brain tumors in MRI images is imperative for precise clinical
diagnosis and treatment. However, existing medical image segmentation methods exhibit …

Brain lesion segmentation provides a valuable tool for clinical diagnosis and research, and
convolutional neural networks (CNNs) have achieved unprecedented success in the …

Clinical diagnosis and treatment decisions rely upon the integration of patient-specific data
with clinical reasoning. Cancer presents a unique context that influences treatment …