Introduction: Traditional neoadjuvant therapy for locally advanced rectal cancer (LARC) results in pathologic complete response (pCR) in approximately 15% of patients, supporting non-operative ...

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 ...

First, we pretrained the encoder of a transformer-based network using a self-supervised approach on unlabeled abdominal computed tomography images. Subsequently, we fine-tuned the segmentation network ...

Hormone replacement therapy (HRT) does not increase breast cancer risk in BRCA1/BRCA2 carriers, with estrogen-alone formulations showing a lower risk. The study used a matched-pair design to control ...

Introduction: Accurate and early identification of brain tumors is essential for improving therapeutic planning and clinical outcomes. Manual segmentation of Magnetic Resonance Imaging (MRI) remains ...

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: The proposed work focuses on using LadderNet for Brain Tumor segmentation using MRI signals through the dataset as an input. The method is helpful in computerized medical analysis. Although ...

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...