Detection of Polyps via Shape and Appearance Modeling

Presented at the MICCAI 2008 Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy, September 6, 2008, New York, USA.This paper describes a CAD system for the detection of colorectal polyps in CT. It is based on stochastic shape and appearance modeling of structures of the colon and rectum, in contrast to the data-driven approaches more commonly found in the literature it derives predictive stochastic models for the features used for classification. The method makes extensive use of medical domain knowledge in the design of the models and in the setting of their parameters. The proposed approach was successfully tested on challenging datasets acquired under a protocol with little colonic preparation; such protocol reduces patient discomfort and potentially improves compliance

Intelligent Interfaces to Empower People with Disabilities

Severe motion impairments can result from non-progressive disorders, such as cerebral palsy, or degenerative neurological diseases, such as Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), or muscular dystrophy (MD). They can be due to traumatic brain injuries, for example, due to a traffic accident, or to brainste

Video Pupil Tracking for Iris Based Identification

Abstract. Currently, iris identification systems are not easy to use since they need a strict cooperation of the user during the snapshot acquisition process. Several acquisitions are generally needed to obtain a workable image of the iris for recognition purpose. To make the system more flexible and open to large public applications, we propose to work on the entire sequence acquired by a camera during the enrolment. Hence the recognition step can be applied on a selected number of the “best workable images ” of the iris within the sequence. In this context, the aim of the paper is to present a method for pupil tracking based on a dynamic Gaussian Mixture Model (GMM) together with Kalman prediction of the pupil position along the sequence. The method has been experimented on a real video sequence captured by a near Infra-Red (IR) sensitive camera and has shown its effectiveness in nearly real time computing.