We present here a new algorithm for segmentation of intensity images which is robust, rapid,
and free of tuning parameters. The method, however, requires the input of a number of …

Segmentation of contrast-enhanced abdominal CT images is required by many clinical
applications of computer aided diagnosis and therapy planning. The research on automated …

Chronic liver disease (CLD), which indicates the inflammatory condition of the liver, leads to
cirrhosis or even partial or total liver dysfunction when left untreated. A non-invasive …

In this paper we present the results of parallelizing two life sciences applications, Markov
random fields-based (MRF) liver segmentation and HMMER's Viterbi algorithm, using GPUs …

This paper presents an automatic liver parenchyma segmentation algorithm that can
segment liver in abdominal CT images. There are three major steps in the proposed …

Determining liver segmentation accurately from MRIs is the primary and crucial step for any
automated liver perfusion analysis, which provides important information about the blood …

In this paper, we present an autocontext model (ACM)-based automatic liver segmentation
algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver …

In this paper, a multi–layer heuristic approach is introduced to segment liver region from
other tissues in multi–slice CT images. Image noise is a principal factor which hampers the …

In this paper, we propose a hybrid approach for fully automatic liver segmentation in
Computed Tomography (CT) data. The approach consists of four stages: first, an intensity …

Liver cancer is the fifth most commonly diagnosed cancer and the third most common cause
of death from cancer worldwide; moreover the liver is the second most commonly involved …