In MRI images, the brain tumor area varies greatly between individuals, and only relying on
the judgment of clinicians is prone to misdiagnosis and misjudgment. Consequently, utilizing …

Accurate and automatic segmentation of pancreatic tumors and organs from medical images
is important for clinical diagnoses and making treatment plans for patients with pancreatic …

While there has been significant progress in AI and neuro-oncologic imaging, clinical utility
remains to be demonstrated. The next wave of progress in this area will be driven by …

Introduction: Accurate diagnosis is crucial for brain tumors, given their low survival rates and
high treatment costs. However, traditional methods relying on manual interpretation of …

Brain tumors in Magnetic resonance image segmentation is challenging research. With the
advent of a new era and research into machine learning, tumor detection and segmentation …

Brain cancers caused by malignant brain tumors are one of the most fatal cancer types with
a low survival rate mostly due to the difficulties in early detection. Medical professionals …

The existing methods for accurate brain tumor (BT) segmentation based on homogeneous
datasets show significant performance degradation in actual clinical applications and lacked …

The accurate segmentation of brain tumor is significant in clinical practice. Convolutional
Neural Network (CNN)-based methods have made great progress in brain tumor …

Simple Summary Computed tomography angiography can provide sufficient information for
the diagnosis of acute aortic syndromes. However, non-contrast computed tomography …

The accurate and fast segmentation method of tumor regions in brain Magnetic Resonance
Imaging (MRI) is significant for clinical diagnosis, treatment and monitoring, given the …