Computerized image capture of structures of interest within...

A - Human Necessities – 61 – B

Patent

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A61B 5/05 (2006.01) G01N 21/27 (2006.01) G01N 33/48 (2006.01) G06T 1/00 (2006.01) G06T 7/40 (2006.01) G06T 7/60 (2006.01)

Patent

CA 2492071

Disclosed is a computerized method (20) for automatically capturing an image of a structure of interest (50) in a tissue sample. The computer memory (100) receives a first pixel data set representing an image of the tissue sample at a low resolution and an identification of a tissue type of the tissue sample, and selecting at least one structure-identification algorithm responsive to the tissue type from a plurality of structure-identification algorithms, at least two of which are responsive to different tissue types. Each structure- identification algorithm correlates at least one cellular pattern in a given tissue type with a presence of a structure of interest (50) for the given tissue type. The method (20) also includes applying the selected structure- identification algorithm to the first pixel dataset to determine a presence of the structure of interest (50) in the tissue sample and capturing a second pixel data set at a high resolution.

L'invention concerne un procédé informatisé de capture automatique d'une image d'une structure d'intérêt dans un échantillon tissulaire. La mémoire de l'ordinateur reçoit un premier ensemble de données pixels représentant une image de l'échantillon tissulaire à faible résolution et une identification d'un type de tissu de l'échantillon tissulaire, puis sélectionne au moins un algorithme structure-identification répondant au type de tissu parmi une pluralité d'algorithmes structure-identification, dont au moins deux répondent aux différents types de tissus. Chaque algorithme structure-identification met en corrélation au moins un modèle cellulaire dans un type de tissu donné en présence d'une structure d'intérêt pour le type de tissu donné. Le procédé consiste également à appliquer l'algorithme structure-identification sélectionné sur le premier ensemble de données pixels afin de déterminer la présence de la structure d'intérêt dans l'échantillon tissulaire, et à capturer un second ensemble de données pixels à haute résolution.

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