A design pattern coupling role and component concepts: Application to medical software

One of the challenges in software development regards the appropriate coupling of separated code elements in order to correctly build initially expected high-level software functionalities. In this context, we address issues related to the dynamic composition of such code elements (i.e. how they are dynamically plugged together) as well as their collaboration (i.e. how they work together). We also consider the limitation of build-level dependencies, to avoid the entire re-compilation and re-deployment of a software when modifying it or integrating new functionalities. To solve these issues, we propose a new design pattern coupling role and component concepts and illustrate its relevance for medical software. Compared to most related works focusing on few role concepts while ignoring others, the proposed pattern integrates many role concepts as first-class entities, including in particular a refinement of the notion of collaboration. Another significant contribution of our proposal concerns the coupling of role and component concepts. Roles are related to the functional aspects of a target software program (composition and collaboration of functional units). Components correspond to the physical distribution of code elements with limited build-level dependencies. As illustrated in this paper, such a coupling enables to instantiate a software program using a generic main program together with a description file focusing on software functionalities only. Related code elements are transparently retrieved and composed at run-time before appropriately collaborating, regardless the specificity of their distribution over components

A graph based image interpretation method using a priori qualitative inclusion and photometric relationships

This paper presents a method for recovering and identifying image regions from an initial oversegmentation using qualitative knowledge of its content. Compared to recent works favoring spatial information and quantitative techniques, our approach focuses on simple a priori qualitative inclusion and photometric relationships such as "region A is included in region B", "the intensity of region A is lower than the one of region B" or "regions A and B depict similar intensities" (photometric uncertainty). The proposed method is based on a two steps" inexact graph matching approach. The first step searches for the best subgraph isomorphism candidate between expected regions and a subset of regions resulting from the initial oversegmentation. Then, remaining segmented regions are progressively merged with appropriate already matched regions, while preserving the coherence with a priori declared relationships. Strengths and weaknesses of the method are studied on various images (grayscale and color), with various intial oversegmentation algorithms (k-means, meanshift, quickshift). Results show the potential of the method to recover, in a reasonable runtime, expected regions, a priori described in a qualitative manner. For further evaluation and comparison purposes, a Python opensource package implementing the method is provided, together with the specifically built experimental database

Approach for sequential image interpretation using a priori binary perceptual topological and photometric knowledge and k-means-based segmentation

International audienc

LiDAR-only based navigation algorithm for an autonomous agricultural robot

The purpose of the work presented in this paper is to develop a general and robust approach for autonomous robot navigation inside a crop using LiDAR (Light Detection And Ranging) data. To be as robust as possible, the robot navigation must not need any prior information about the crop (such as the size and width of the rows). The developed approach is based on line extractions from 2D point clouds using a PEARL based method. In this paper, additional filters and refinements of the PEARL algorithm are presented in the context of crop detection. A penalization of outliers, a model elimination step, a new model search and a geometric constraint are proposed to improve the crop detection. The approach has been tested over a simulator and compared with classical PEARL and RANSAC based approaches. It appears that adding those modification improved the crop detection and thus the robot navigation. Those results are presented and discussed in this paper. It can be noticed that even if this paper presents simulated results (to ease the comparison with other algorithms), the approach also has been successfully tested using an actual Oz weeding robot, developed by the French company Naio Technologies

An interactive medical image segmentation system based on the optimal management of regions of interest using topological medical knowledge

This paper presents an original interactive system for efficient medical image segmentation in computer aided diagnosis. The main originality concerns the method used to manage, according to an a priori topological-based structural model, regions of interest (ROIs) within which computations can be constrained. The goal is then to avoid the processing of irrelevant image points, therefore improving and accelerating segmentations. In the case of a hierarchical modeling procedure, our ROI management method enables, for delineating a given medical structure, to optimally determine image points of interest by taking previously segmented structures into account. We propose a mathematical formulation of the method as well as a possible implementation within an interactive system. We also detail an experience report focussing on the segmentation of several abdominal structures from a CT image. It illustrates the behavior and the potential of our method

Region-based active contours for computer-aided analysis of carotid Phase Contrast MRI

International audienc

Python based internet tools in contriol education

The general language and opensource Python, coupled with its scientific libraries, offers an interesting alternative to Matlab, Java, and C++ for the development of scientific applications. In this context, authors present the main features of the language, associated tools, architecture and the diversity of its scientific environment. Three applications related to control education are presented: programming from a web browser (for system identification and PID tuning) and embedded computing (for motors control)