Cloud–based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks

Abstract—Variations in the shape and appearance of anatomical structures in medical images are often relevant radiological signs of disease. Automatic tools can help automate parts of this manual process. A cloud–based evaluation framework is presented in this paper including results of benchmarking current state–of–the–art medical…

A new method for the automatic retrieval of medical cases based on the RadLex ontology

Abstract Purpose The goal of medical case-based image retrieval (M-CBIR) is to assist radiologists in the clinical decision making process by finding medical cases in large archives that most resemble a given case. Cases are described by radiology reports comprised of radiological images and…

3D segmentation using perceptual computing

Abstract We present a semi-automatic tool for 3D segmentation in volumetric medial sans using natural input from the user. The input onsists of hand motions and gestures aquired using 3D amera. Our method onsists of ve steps: 1) initial 2D…

Automatic liver tumor segmentation in follow-up CT studies using Convolutional Neural Networks

Abstract We present a new, fully automatic algorithm for liver tumors seg-mentation in follow-up CT studies. The inputs are a baseline CT scan and a de-lineation of the tumors in it and a follow-up scan; the outputs are the tumors…

Tumor burden evaluation in NF1 patients with plexiform neurofibromas in daily clinical practice

Abstract Background Existing volumetric measurements of plexiform neurofibromas (PNs) are time consuming and error prone, as they require delineation of PN boundaries, a procedure that is not practical in the typical clinical setting. The aim of this study is to…

Automatic lung tumor segmentation with leaks removal in follow-up CT studies

Abstract Purpose In modern oncology, disease progression and response to treatment are routinely evaluated with a series of volumetric scans. The number of tumors and their volume (mass) over time provides a quantitative measure for the evaluation. Thus, many of…

The Effect of Chemotherapy on Optic Pathway Gliomas and Their Sub-Components: A Volumetric MR Analysis Study

Abstract Background. Optic pathway gliomas (OPG) represent 5% of pediatric brain tumors and compose a major therapeutic dilemma to the treating physicians. While chemotherapy is widely used for these tumors, our ability to predict radiological response is still lacking. In…

Schizophrenia patients di erentiation based on MR vascular perfusion and volumetric imaging

Abstract Candecomp/Parafac Decomposition (CPD) has emerged as a framework for modeling N-way arrays (higher-order matrices). CPD is naturally well suited for the analysis of data sets comprised of observations of a function of multiple discrete indices. In this study we…

Medical case-based retrieval of patient records using the RadLex hierarchical lexicon

Abstract We present a new method for the retrieval radiological cases from a database of clinical cases described by terms from the RadLex lexicon. The input is an database of cases and a query consisting of the patient volumetric scan,…

Coronal tibiofemoral subluxation: a new measurement method

Abstract Background: Coronal tibiofemoral (CTF) subluxation is a common finding in knee osteoarthritis (OA) which can be related to poor pain scores and tibial spine impingement. In this study we describe a new method for measuring CTF subluxation and present…

Semiautomatic segmentation and follow-up of multicomponent low-grade tumors in longitudinal brain MRI studies

Abstract Purpose: Tracking the progression of low grade tumors (LGTs) is a challenging task, due to their slow growth rate and associated complex internal tumor components, such as heterogeneous enhancement, hemorrhage, and cysts. In this paper, the authors show a…

PNist: interactive volumetric measurements of plexiform neurofibromas in MRI scans

Abstract Purpose Volumetric measurements of plexiform neurofibromas (PNs) are time consuming and error prone, as they require the delineation of the PN boundaries, which is mostly impractical in the daily clinical setup. Accurate volumetric measurements are seldom performed for these…

Rule-Based Ventral Cavity Multi-Organ Automatic Segmentation in CT Scans

Abstract We describe a new method for the automatic segmentation of multiple organs of the ventral cavity in CT scans. The method is based on a set of rules that determine the order in which the organs are isolated and…

Automatic lung tumor segmentation with leaks removal in follow-up CT studies

Abstract We present a novel automatic algorithm for lung tumors segmentation in follow-up CT studies. The inputs are a baseline CT scan and a delineation of the tumors in it; the output is the tumor delineations in the follow-up scan.…

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