Automated Segmentation of Cytological and Histological
Images for the Nuclear 
Quantification: an Adaptive Approach based 
 on Mathematical Morphology

Elmoataz, Abderrahim; Belhomme, Philippe; Herlin, Paulette; Schüpp, Sophie; Revenu, Marinette; Bloyet, Daniel

doi:10.1051/mmm:1996130

Cited by 2 publications

(1 citation statement)

References 5 publications

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“…Our first two IP plans have enabled to validate the TMT model and the system's architecture by taking into account actual applications. They were developed in our research team by A. Elmoataz (Elmoataz et al, 1996) and F. Angot (Angot, 1999) to process biomedical images of cytology and histology provided by the cancer-research centre F. Baclesse of Caen.…”

Section: Validation Of Model and Architecturementioning

confidence: 99%

CBR for the management and reuse of image-processing expertise: a conversational system

Ficet-Cauchard

Porquet

Revenu

1999

Engineering Applications of Artificial Intelligence

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International audienceThe development of an image-processing (IP) application is a complex activity, which can be greatly alleviated by user-friendly graphical programming environments. The major objective of the work described in this paper is to help IP experts reuse parts of their applications. A first step towards knowledge reuse has been to propose a suitable representation of the strategies of IP experts by means of IP plans (trees of tasks, methods and tools). This paper describes the CBR module of an interactive system for the development of IP plans. After a brief presentation of the overall architecture of the system and its other modules, the authors explain the distinction between an IP case and an IP plan, and give the selection criteria and functions that are used for similarity calculation. The core of the CBR module is a search/adaptation algorithm, whose main steps are detailed: retrieval of suitable cases, recursive adaptation of the selected one and memorization of new cases. The system's implementation is presently completed; its functioning is described in a session showing the kind of assistance provided by the CBR module during the development of a new IP application

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Section: Validation Of Model and Architecturementioning

confidence: 99%