Towards Touch-Based Medical Image Diagnosis Annotation
Francisco Maria Calisto, Alfredo Ferreira, Jacinto C. Nascimento, Daniel Jorge Viegas Gonçalves · 2017
A fundamental step in medical diagnosis for patient follow-up relies on the ability of radiologists to perform a trusty diagnostic from acquired images. Basically, the diagnosis strongly depends on the visual inspection over the shape of the lesions. As datasets increase in size, such visual evaluation becomes harder. For this reason, it is crucial to introduce easy-to-use interfaces that help the radiologists to perform a reliable visual inspection and allow the efficient delineation of the lesions. We will explore the radiologist's receptivity to the current touch environment solution. The advantages of touch are threefold: (i) the time performance is superior regarding the traditional use, (ii) it has more intuitive control and, (iii) for less time, the user interface delivers more information per action, concerning annotations. From our studies, we conclude that the radiologists still exhibit a resistance to change from traditional to touch based interfaces in current clinical setups.