Background: The proposed Architecture will provide the processing and analysis essential to accurate and reliable detection of brain tumors from MRI, for timely diagnosis and evidence-based decisions.

Abstract: Tumor segmentation is crucial for surgical planning and precise tumor resection for effective treatment. Traditionally, tumor localization has been performed using medical imaging techniques ...

Medical image segmentation plays a vital role in diagnostic imaging, particularly for measuring brain tumor morphology in MRI scans, which directly influences treatment planning, prognosis, and ...

Tumor segmentation in lung CT using U-Net, U-Net++ and an augmentation-enhanced U-Net. Best validation Dice: 0.807 (MSD lung dataset).

Abstract: Brain tumor segmentation, Delineating tumor areas from a fin-n-healthy brain tissue in medical pictures is critical for proper diagnosis, planning of treatment, and observing alignment ...

ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...

ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...

SAN DIEGO, July 30, 2025 /PRNewswire/ -- Cortechs.ai, a pioneer in AI-powered medical imaging solutions, is pleased to announce the immediate availability of its latest release of the FDA-cleared ...