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Anais do IHC'2001 - Departamento de Informática e Estatística - UFSC

Anais do IHC'2001 - Departamento de Informática e Estatística - UFSC

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<strong>Anais</strong> <strong>do</strong> IHC’2001 - IV Workshop sobre Fatores Humanos em Sistemas Computacionais 297<br />

Structuring the Space of Interaction Practices in the<br />

Segmentation of Medical Images: a First Discussion<br />

Sílvia D. Olabarriaga and Marcelo S. Pimenta<br />

Instituto <strong>de</strong> <strong>Informática</strong> – Universida<strong>de</strong> Fe<strong>de</strong>ral <strong>do</strong> Rio Gran<strong>de</strong> <strong>do</strong> Sul (UFRGS)<br />

Caixa Postal 15.064 – 91.501-970 – Porto Alegre – RS – Brazil<br />

{silvia,mpimenta}@inf.ufrgs.Br<br />

Abstract. This paper presents a first discussion on how to structure the space of<br />

interaction practices in the segmentation of medical images. We first present an<br />

example of application to set a scenario for discussion. Next we summarize some<br />

of the interactive aspects related to image segmentation methods. Finally we<br />

present some initial i<strong>de</strong>as about how to improve the <strong>de</strong>sign of ISMs with HCI<br />

metho<strong>do</strong>logy.<br />

1. Introduction<br />

Segmentation is a step in the analysis of digital images where the object of interest is<br />

isolated from the background [Gonzalez and Woods (1993)]. Segmentation supports<br />

several analysis tasks such as quantification, inspection and retrieval; in all cases,<br />

automatic processing is <strong>de</strong>sirable, but sometimes unattainable due to limitations imposed<br />

by image acquisition, abnormalities in the scene, or both. Interactive segmentation methods<br />

(ISMs) are a<strong>do</strong>pted in applications with a high <strong>de</strong>mand for accurate results, when the<br />

volume of images is reasonable, and when the image dimensionality admits human<br />

manipulation.<br />

As a general rule, the goal of ISMs is to combine a human operator and a computer<br />

(also named computational part) to obtain an accurate <strong>de</strong>lineation of the object of interest<br />

in an efficient manner. The un<strong>de</strong>rlying assumption is that the user knows the correct<br />

<strong>de</strong>lineation and, as such, he/she could gui<strong>de</strong> the computational part to <strong>de</strong>termine it<br />

efficiently. This is the case of many applications, in particular in the medical field, where<br />

clinical practice and research impose several <strong>de</strong>mands on reliability of results obtained with<br />

or by computational tools.<br />

In this short paper we start a discussion on how to structure the space of interaction<br />

practices in the segmentation of medical images. We first present an example of application<br />

to set a scenario for discussion. Next we present a review of aspects related to interactive<br />

segmentation methods. Finally we present some initial i<strong>de</strong>as about how to improve the<br />

<strong>de</strong>sign of ISMs with HCI metho<strong>do</strong>logy.<br />

2. A simple example of interactive segmentation in medical imaging<br />

As an example of interactive segmentation procedures, consi<strong>de</strong>r the following scenario: a<br />

pregnant woman is submitted to ultrasound (US) to check the baby's <strong>de</strong>velopment, which is<br />

roughly assessed by the diameter of the baby's head. The <strong>do</strong>ctor manipulates the US probe<br />

on the belly, trying to get the best view of the head on the screen, such that its diameter can<br />

be most reliably estimated. The image is “frozen” when the <strong>do</strong>ctor is satisfied and then

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