Evaluation of monoscopic and stereoscopic displays for visual-spatial tasks in medical contexts.

In the medical field, digital images are present in diagnosis, pre-operative planning, minimally invasive surgery, instruction, and training. The use of medical digital imaging has afforded new ways to interact with a patient, such as seeing fine details inside a body. This increased usage also raises many basic research questions on human perception and performance when utilizing these images. The work presented here attempts to answer the question: How would adding the stereopsis depth cue affect relative position tasks in a medical context compared to a monoscopic view? By designing and conducting a study to isolate the benefits between monoscopic 3D and stereoscopic 3D displays in a relative position task, the following hypothesis was tested: stereoscopic 3D displays are beneficial over monoscopic 3D displays for relative position judgment tasks in a medical visualization setting. 44 medical students completed a series of relative position judgments tasks. The results show that stereoscopic condition yielded a higher score than the monoscopic condition with regard to the hypothesis.

Evaluating mental workload of two-dimensional and three-dimensional visualization for anatomical structure localization.

Visualization of medical data in three-dimensional (3D) or two-dimensional (2D) views is a complex area of research. In many fields 3D views are used to understand the shape of an object, and 2D views are used to understand spatial relationships. It is unclear how 2D/3D views play a role in the medical field. Using 3D views can potentially decrease the learning curve experienced with traditional 2D views by providing a whole representation of the patient's anatomy. However, there are challenges with 3D views compared with 2D. This current study expands on a previous study to evaluate the mental workload associated with both 2D and 3D views. Twenty-five first-year medical students were asked to localize three anatomical structures--gallbladder, celiac trunk, and superior mesenteric artery--in either 2D or 3D environments. Accuracy and time were taken as the objective measures for mental workload. The NASA Task Load Index (NASA-TLX) was used as a subjective measure for mental workload. Results showed that participants viewing in 3D had higher localization accuracy and a lower subjective measure of mental workload, specifically, the mental demand component of the NASA-TLX. Results from this study may prove useful for designing curricula in anatomy education and improving training procedures for surgeons.

Colorization of CT images to improve tissue contrast for tumor segmentation.

Segmenting tumors from grayscale medical image data can be difficult due to the close intensity values between tumor and healthy tissue. This paper presents a study that demonstrates how colorizing CT images prior to segmentation can address this problem. Colorizing the data a priori accentuates the tissue density differences between tumor and healthy tissue, thereby allowing for easier identification of the tumor tissue(s). The method presented allows pixels representing tumor and healthy tissues to be colorized distinctly in an accurate and efficient manner. The associated segmentation process is then tailored to utilize this color data. It is shown that colorization significantly decreases segmentation time and allows the method to be performed on commodity hardware. To show the effectiveness of the method, a basic segmentation method, thresholding, was implemented with and without colorization. To evaluate the method, False Positives (FP) and False Negatives (FN) were calculated from 10 datasets (476 slices) with tumors of varying size and tissue composition. The colorization method demonstrated statistically significant differences for lower FP in nine out of 10 cases and lower FN in five out of 10 datasets.

Development of a customizable software application for medical imaging analysis and visualization.

Graphics technology has extended medical imaging tools to the hands of surgeons and doctors, beyond the radiology suite. However, a common issue in most medical imaging software is the added complexity for non-radiologists. This paper presents the development of a unique software toolset that is highly customizable and targeted at the general physicians as well as the medical specialists. The core functionality includes features such as viewing medical images in two-and three-dimensional representations, clipping, tissue windowing, and coloring. Additional features can be loaded in the form of 'plug-ins' such as tumor segmentation, tissue deformation, and surgical planning. This allows the software to be lightweight and easy to use while still giving the user the flexibility of adding the necessary features, thus catering to a wide range of user population.

A collaborative interaction and visualization multi-modal environment for surgical planning.

The proliferation of virtual reality visualization and interaction technologies has changed the way medical image data is analyzed and processed. This paper presents a multi-modal environment that combines a virtual reality application with a desktop application for collaborative surgical planning. Both visualization applications can function independently but can also be synced over a network connection for collaborative work. Any changes to either application is immediately synced and updated to the other. This is an efficient collaboration tool that allows multiple teams of doctors with only an internet connection to visualize and interact with the same patient data simultaneously. With this multi-modal environment framework, one team working in the VR environment and another team from a remote location working on a desktop machine can both collaborate in the examination and discussion for procedures such as diagnosis, surgical planning, teaching and tele-mentoring.