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…

Accuracy of computer-aided techniques in orthopaedic surgery: how can it be defined, measured experimentally, and analyzed from a clinical perspective

Surgical accuracy is multifactorial – it is therefore crucial to take into account all influencing factors when investigating the accuracy of a surgical gesture, such as the surgeon’s experience, local difficulties associated with the specific anatomical site and the assistive technologies that may…

The influence of varying the number of characters per row on the accuracy and reproducibility of the ETDRS visual acuity chart

Background As part of an effort to improve upon the Snellen chart, we provide a standardized version of the ETDRS chart utilizing five characters in each row. The choice of five characters contradicts the recommended ten characters per row determined by the NAS-NRC, a…

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…

Detection and correction of volumetric medical image segmentation errors by 3D-ray casting and Laplace deformation

Abstract Purpose Patient-specific models of anatomical structures and pathologies generated from volumetric medical images play an increasingly central role in many aspects of patient care. A key task in generating these models is the segmentation of anatomical structures and pathologies of interest. Although numerous…

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…

Haptic computer-assisted patient-specific preoperative planning for orthopedic fractures surgery

Abstract Purpose The aim of orthopedic trauma surgery is to restore the anatomy and function of displaced bone fragments to support osteosynthesis. For complex cases, including pelvic bone and multi-fragment femoral neck and distal radius fractures, preoperative planning with a…

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…

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