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…

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…

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.…

Fast MRI for repeated scans

Abstract Radiological assessment of brain disease progression and response to therapy is often performed with repeated MRI scans acquired every few weeks/months. In these longitudinal studies, each scan is acquired anew without taking into account the information present in previous…

Reduced-dose patient to baseline CT rigid registration in 3D Radon space

Abstract We present a new method for rigid registration of CT scans in Radon space. The inputs are the two 3D Radon transforms of the CT scans, one densely sampled and the other sparsely sampled. The output is the rigid…

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

Abstract This study presents a haptic-based patient specific preoperative planning tool for orthopedic surgeries designed to restore pelvic bone fractures. The tool allows planning of both of mains steps of an orthopedic surgery: reduction and fixation. The planning is carry…

Image Segmentation Errors Correction by Mesh Segmentation and Deformation

Abstract Volumetric image segmentation methods often produce delineations of anatomical structures and pathologies that require user modifications. We present a new method for the correction of segmentation errors. Given an initial geometrical mesh, our method semi automatically identifies the mesh…

Brain Tissue Deformation Tracking with a Paraboloid Model for Outlier Detection

Abstract This paper describes a new method for real-time quantification of brain shift during craniotomy surgery. Our method estimates the deformation on the visible surface of the brain by tracking the 3D location of automatically selected points on the brain…

Automatic Bone Fracture Reduction by Fracture Contact Surface Identification and Registration

Abstract Bone fracture reduction is an essential step in the treatment of orthopedic fractures. It consists of determining the position and orientation of the fractured bone fragments for their fixation with implants. This paper presents a new method for the…

Deep brain stimulation surgery time reduction based on the automatic detection of the subthalamic nucleus: method and preliminary results

Abstract. Deep brain stimulation (DBS) surgery of the subthalamic nucleus (STN) is an effective therapy in the management of the motor symptoms of advanced Parkinson’s disease (PD). The accurate localization of the STN is essential to achieve an optimal outcome…

Anatomical structures segmentation by spherical 3D ray casting and gradient domain editing

Abstract Fuzzy boundaries of anatomical structures in medical images make segmentation a challenging task. We present a new segmentation method that addresses the fuzzy boundaries problem. Our method maps the lengths of 3D rays cast from a seed point to…

Prediction of Brain MR Scans in Longitudinal Tumor Follow-Up Studies

Abstract We present a new method for the estimation of the next brain MR scan in a longitudinal tumor follow-up study. Our method effectively incorporates information of the past scans in the time series to predict the future scan of…

Trajectory Planning with Augmented Reality for Improved Risk Assesment in Image-guided Keyhole Neurosurgery

Abstract We present a new preoperative planning method for reducing the risk associated with the insertion of straight tools in image-guided keyhole neurosurgery. The method quantifies the risks of multiple candidate trajectories and presents them on a physical model of…

Longitudinal Assessment of Brain Tumors Using a Repeatable Prior-based Segmentation

Abstract This paper presents an automatic method for a repeatable, prior-based segmentation and classification of brain tumors in longitudinal MR scans. The method is designed to overcome the inter/intra observer variability and to provide a repeatable delineation of the tumor…

Spectral-based 2D/3D X-ray to CT image rigid registration

Abstract We present a spectral-based method for the 2D/3D rigid registration of X-ray images to a CT scan. The method uses a Fourier-based representation to decompose the six rigid transformation parameters problem into a twoparameter out-of-plane rotation and a four-parameter…

Plexiform Neurofibroma tissue classification

Abstract Plexiform Neurofibroma (PN) is a major complication of NeuroFibromatosis-1 (NF1), a common genetic disease that involving the nervous system. PNs are peripheral nerve sheath tumors extending along the length of the nerve in various parts of the body. Treatment…

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