This paper presents a landmark-based parametric 3D foot model which can be used as the basis for designing customised shoe lasts. 22 points on the surface of the foot are defined as anthropometric landmarks.11 NURBS curves are then generated based on these 22 landmarks to construct the 3D parametric foot surface model using Rhinoceros® and Grasshopper®. Nineteen test subjects participated in an experiment to verify the effectiveness of the proposed model. The mean absolute difference of the ball girth between the 19 models and their corresponding 3D scans was found as 3.53 mm. The mean directed Hausdorff distance between the foot outlines of the models and the 3D scans was identified as 1.40 mm. Regarding the 3D surface, the overall mean bidirectional mean directed Hausdorff distance between the models and the 3D scans of all 19 cases was calculated as 3.68 ± 0.31 mm. Compared to the findings of other researchers, it is concluded that the proposed parametric model can describe the 3D shape of the foot with a reasonable accuracy and it can be used as a basis for shoe last design.

HCI plays an important role in interactive medical image segmentation. The Goals, Operators, Methods, and Selection rules (GOMS) model and the National Aeronautics and Space Administration Task Load Index (NASA-TLX) questionnaire are different methods that are often used to evaluate the HCI process. In this article, we aim at improving the HCI process of interactive segmentation using both the GOMS model and the NASA-TLX questionnaire to: 1) identify the relations between these two methods and 2) propose HCI design suggestions based on the synthesis of the evaluation results using both methods. For this, we conducted an experiment where three physicians used two interactive segmentation approaches to segment different types of organs at risk for radiotherapy planning. Using the GOMS model, we identified 16 operators and 10 methods. Further analysis discovered strong relations between the use of GOMS operators and the results of the NASA-TLX questionnaire. Finally, HCI design issues were identified, and suggestions were proposed based on the evaluation results and the identified relations.

Findings from previous literatures, ethnography studies and interviews showed that radiotherapy contouring interfaces are very complex, requiring many human-computer interactions (HCI). In this paper we used observational, heuristic evaluation, think aloud and NASA-TLX methods to 1) analyse the workflow of radiotherapy segmentation systems; 2) discover possible usability and HCI design issues of current segmentation systems in order to identify the requirements for future interface design; and 3) explore the abilities and limitations of various evaluation methods. From the results it can be seen that observational and think aloud methods were very useful in identifying the workflow of different systems. The heuristic evaluation method uncovered more general usability issues with the interface design. The think aloud method identified more HCI issues compared to general usability issues. From the NASA-TLX, it can be seen that the workload level of system C is higher in almost all the categories. Using the four different methods this study identified several usability and HCI issues and have proposed seven main requirements which might be considered in our future studies.

Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians' expertise and computers' potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the "strokes" and the "contour", to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design.

During the radiotherapy planning process patient’s medical images are used to determine the optimum configuration of radiation beams for their cancer treatment. The primary aim of radiotherapy planning is to maximize radiation dose to the patient’s tumour while sparing their normal tissues. To achieve this, the boundary of the tumour needs to be accurately identified in the treatment planning process, especially in the step of target volume delineation. Clinically, tumour delineation is performed by physicians, either manually or using semi-automatic/automatic software based on the patient’s CT, PET and/or MRI images. In addition to the expertise of the physician and choices of segmentation algorithms, the usability of the software also plays an important role in the tumour delineation process. In this paper, the usability of the IPLAN ® contouring software was evaluated. First, two evaluators assessed the software according to the heuristic evaluation method. Then three physicians evaluated the same system using the think aloud method. The outcomes of the experiments revealed different insights of the system. With the think aloud method, it was easier to identify end users’ preferences regarding both software interface and hardware input tools. On the other hand, the heuristic evaluation method uncovered more specific issues with the interface. Besides, this method was able to explore more details regarding individual functionalities on the interface. Based on the comparison of the outcomes of both methods, it is suggested that in the process of improving usability of the contouring interface, the think aloud method can be applied to explore preferences of the user. The heuristic evaluation can be applied in designing the details of the interface.