Computer science advances and ultra-fast computing speeds find artificial intelligence (AI) broadly benefitting modern society-forecasting weather, recognizing faces, detecting fraud, and deciphering genomics. AI's future role in medical practice rem...
PURPOSE: This paper studies the feasibility of developing a fast and accurate automatic kidney component segmentation method. The proposed method segments the kidney into four components: renal cortex, renal column, renal medulla, and renal pelvis.
Proceedings of the National Academy of Sciences of the United States of America
Nov 7, 2017
Some microbes possess the ability to adaptively manipulate host behavior. To better understand how such microbial parasites control animal behavior, we examine the cell-level interactions between the species-specific fungal parasite and its carpente...
Many automatically analyzable scientific questions are well-posed and a variety of information about expected outcomes is available a priori. Although often neglected, this prior knowledge can be systematically exploited to make automated analysis op...
Salient object detection from RGB-D images aims to utilize both the depth view and RGB view to automatically localize objects of human interest in the scene. Although a few earlier efforts have been devoted to the study of this paper in recent years,...
OBJECTIVE: Focal cortical dysplasias (FCDs) often cause pharmacoresistant epilepsy, and surgical resection can lead to seizure-freedom. Magnetic resonance imaging (MRI) and positron emission tomography (PET) play complementary roles in FCD identifica...
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Oct 30, 2017
Accurate quantification of uptake on PET images depends on accurate attenuation correction in reconstruction. Current MR-based attenuation correction methods for body PET use a fat and water map derived from a 2-echo Dixon MRI sequence in which bone ...
Journal of computational biology : a journal of computational molecular cell biology
Oct 30, 2017
Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a ...
With the growing use of minimally invasive surgical procedures, endoscopic video archives are growing at a rapid pace. Efficient access to relevant content in such huge multimedia archives require compact and discriminative visual features for indexi...
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.
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