Cure rates for kidney cancer vary according to stage and grade; hence, accurate diagnostic
procedures for early detection and diagnosis are crucial. Some difficulties with manual …

Recent breakthroughs of deep learning algorithms in medical imaging, automated detection,
and segmentation techniques for renal (kidney) in abdominal computed tomography (CT) …

Background: We directly compared the mammography image processing results obtained
with the help of the YOLOv4 convolutional neural network (CNN) model versus those …

Renal cancer is one of the ten most common cancers in the population that affects 65,000
new patients a year. Nowadays, to predict pathologies or classify tumors, deep learning (DL) …

Abstract The Kidney and Kidney Tumor Segmentation Challenge 2021 (KiTS21) released a
kidney CT dataset with 300 patients. Unlike KiTS19, KiTS21 provided a cyst category …

Background Kidney tumors have become increasingly prevalent among adults and are now
considered one of the most common types of tumors. Accurate segmentation of kidney …

Recent breakthroughs of deep learning algorithms in medical imaging, automated detection,
and segmentation techniques for renal (kidney) in abdominal computed tomography (CT) …

Kidney tumor segmentation is a difficult task because of the complex spatial and volumetric
information present in medical images. Recent advances in deep convolutional neural …

Early and accurate breast cancer detection is crucial for effective intervention and improved
patient outcomes. Conventional methods often encounter challenges in achieving the …

There are more than 400,000 new cases of kidney cancer each year, and surgery is its most
common treatment. Accurate segmentation and characterization of kidneys and kidney …