Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we proposed a general fram...
Dongfeng Han, John E. Bayouth, Qi Song, Aakant Tau...
We present a fast graph cut algorithm for planar graphs.
It is based on the graph theoretical work [2] and leads to an
efficient method that we apply on shape matching and im-
a...
For quantitative analysis of histopathological images,
such as the lymphoma grading systems, quantification of
features is usually carried out on single cells before categorizing...
Hui Kong, Metin Gurcan, and Kamel Belkacem-Boussai...
We studied a method using support vector machines (SVMs) with walk-based graph kernels for the high-level feature extraction (HLF) task. In this method, each image is first segmen...
This paper proposes an automatic foreground segmentation system based on Gaussian mixture models and dynamic graph cut algorithm. An adaptive perpixel background model is develope...