Assessment of renal function and structure accurately remains essential in the diagnosis
and prognosis of Chronic Kidney Disease (CKD). Advanced imaging, including Magnetic …

Background and objective Segmentation is an essential step in computer-aided diagnosis
and treatment planning of kidney diseases. In recent years, several researchers proposed …

Objectives To develop a 3D U-Net-based deep learning model for automated segmentation
of kidney and renal mass, and detection of renal mass in corticomedullary phase of …

Abstract Background and Purpose The precise kidney segmentation is very helpful for
diagnosis and treatment planning in urology, by giving information about malformation in the …

This paper presents a systematic literature review concerning 3D segmentation algorithms
for computerized tomographic imaging. This analysis covers articles published in the range …

Abdominal computed tomography (CT) data are often used in the diagnosis and treatment of
patients. Segmentation of viscera on abdominal imaging facilitates diagnosis and focus …

This study focused on the application of deep learning algorithms in the segmentation of CT
images, so as to diagnose chronic kidney diseases accurately and quantitatively. First, the …

Identification of FDGavid-neoplasms may be obscured by high-uptake normal tissues, thus
limiting inferences about the natural history of disease. We introduce a FDG-PET radiomics …

Organ segmentation is an important step in Ultrasound fetal images for early prediction of
congenital abnormalities and to estimate delivery date. In many applications of 2D medical …

In this document, we employed an efficient Optimal GLCM attribute related FCM
segmentation algorithm which is used to categorize the kidney cysts and tumor from the …