Tumor segmentation in Computed Tomography (CT) images is a crucial step in image-
guided surgery. However, low-contrast CT images impede the performance of subsequent …

Background and Objective B-spline interpolation (BSI) is a popular technique in the context
of medical imaging due to its adaptability and robustness in 3D object modeling. A field that …

Image processing by segmentation technique is an important phase in medical imaging
such as MRI. Its objective is to analyze the different tissues in human body. In research area …

Pore-scale modeling, aided by imaging advancements and computational power, is now a
vital tool for comprehending fluid flow and transport in porous media. It allows detailed …

Accurate and fast liver segmentation remains a challenging and important task for clinicians.
Segmentation algorithms are slow and inaccurate due to noise and low quality images in …

Automated and accurate liver vessel segmentation is essential for clinical diagnosis and
treatment, but the segmentation of small vessels still remains challenging due to their …

Cross-modal medical imaging techniques are predominantly being used in the clinical suite.
The ensemble learning methods using cross-modal medical imaging adds reliability to …

Abstract Background The Otsu method and the Chan–Vese model are two methods proven
to perform well in determining volumes of different organs and specific tissue fractions. This …

Contrast is an imperative perceptible attribute embodying the image quality. In medical
images, the poor quality specifically low contrast inhibits precise interpretation of the image …

Obtaining rapid and accurate segmentation of organs remains an important and challenging
task. Liver segmentation algorithms are slow and inaccurate due to noise and low-quality …