Abstract: Accurate liver and tumor segmentation in CT images is vital for diagnosis and treatment planning. This study presents SegResNet_2335, a lightweight 3D residual network optimized for ...

As shown below, the inferred masks predicted by our segmentation model trained by the dataset appear similar to the ground truth masks. This repository contains a curated and enhanced version of brain ...

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 ...

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

What if the programming language you rely on most is on the brink of a transformation? For millions of developers worldwide, Python is not just a tool, it’s a cornerstone of their craft, powering ...

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 ...

Researchers at Tsinghua University have released a novel Python toolkit, scLT-kit, which automates the processing and analysis of single-cell lineage tracing data, delivering clear insights into how ...

Adult patients with CRC with synchronous CRLM (N = 57) at Mayo Clinic were identified from the electronic health record. Routine tumor hematoxylin and eosin sections were digitized and reviewed for ...

JSKN003, a biparatopic anti-HER2 antibody drug conjugate (ADC), in the treatment of platinum-resistant ovarian cancer (PROC): Updated findings from two clinical trials. This is an ASCO Meeting ...