This paper presents a novel hybrid segmentation technique incorporating a statistical as well as a geometric model in a unified segmentation scheme for brain tissue segmentation o...
Albert Huang, Rafeef Abugharbieh, Roger Tam, Antho...
Abstract. This paper describes effort towards automatic tissue segmentation in neonatal MRI. Extremely low contrast to noise ratio (CNR), regional intensity changes due to RF coil ...
Guido Gerig, Marcel Prastawa, Weili Lin, John H. G...
This paper presents a fully automated segmentation method for medical images. The goal is to localize and parameterize a variety of types of structure in these images for subsequen...
Tumor segmentation from MRI data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in...
Albert Murtha, Dana Cobzas, Mark Schmidt, Martin J...
We introduce a novel approach for magnetic resonance image (MRI) brain tissue classification by learning image neighborhood statistics from noisy input data using nonparametric den...
Tolga Tasdizen, Suyash P. Awate, Ross T. Whitaker,...