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

Recently, several recurrent neural network (RNN)-based models have been proposed to
delineate the outlines of buildings from very high resolution (VHR) remote sensing images …

Purpose Fast and accurate auto-segmentation on daily images is essential for magnetic
resonance imaging (MRI)–guided adaptive radiation therapy (ART). However, the state-of …

Purpose Cerebral vasospasm following aneurysmal subarachnoid hemorrhage (aSAH) is a
significant complication associated with poor neurological outcomes. We present a novel …

Purpose Advanced image segmentation techniques like the Chan-Vese (CV) models
transform the segmentation problem into a minimization problem which is then solved using …

With state-of-the-art imaging and analytical tools onboard the NASA Perseverance Rover
Mission, geological information for remote astrobiological analysis is readily available and …

Objective-Medical image segmentation is essential for several clinical tasks, including
diagnosis, surgical and treatment planning, and image-guided interventions. Deep Learning …

Diseases can be diagnosed and monitored by extracting regions of interest (ROIs) from
medical images. However, accurate and efficient delineation and segmentation of ROIs in …

With the increasing integration of functional imaging techniques like Positron Emission
Tomography (PET) into radiotherapy (RT) practices, a paradigm shift in cancer treatment …

The level set is a classical image segmentation model. In order to achieve its stable
evolution, the level set function should be a signed distance function (SDF). However, due to …