KEYWORDS: Stereoscopic displays, Surgery, Visualization, 3D image processing, 3D displays, 3D modeling, Stereoscopy, Computed tomography, Blood vessels, Magnetic resonance imaging
In this paper we review empirical studies that investigate performance effects of stereoscopic displays for medical
applications. We focus on four distinct application areas: diagnosis, pre-operative planning, minimally invasive surgery
(MIS) and training/teaching. For diagnosis, stereoscopic displays can augment the understanding of complex spatial
structures and increase the detection of abnormalities. Stereoscopic viewing of medical data has proven to increase the
detection rate in breast imaging. A stereoscopic presentation of noisy and transparent images in 3D ultrasound results in
better visualization of the internal structures, however more empirical studies are needed to confirm the clinical
relevance. For MRI and CT, where images are frequently rendered in 3D perspective, the added value of binocular depth
has not yet been convincingly demonstrated. For MIS, stereoscopic displays can decrease surgery time and increase
accuracy of surgical procedures. Performance of surgical procedures is similar when high resolution 2D displays are
compared with lower resolution stereoscopic displays, indicating an image quality improvement for stereoscopic
displays. Training and surgical planning already use computer simulations in 2D, however more research is needed to the
benefit of stereoscopic displays in those applications. Overall there is a clear need for more empirical evidence that
quantifies the added value of stereoscopic displays in medical domains, such that the medical community will have
ample basis to invest in stereoscopic displays in all or some of the described medical applications.
Display image quality, image reproducibility and compliance to standards are getting more and more important. It is
known that LCDs suffer from viewing angle dependency, meaning that the characteristics of the LCD change with
viewing angle.
Display calibration and corresponding quality checks typically take place for on-axis viewing. However, users typically
use their display under a rather broad range of viewing angles. Several studies have shown that when calibration is done
for on-axis viewing then the display is not accurately complying with the standard when viewing off-axis.
A possible solution is tracking the position of the user in
real-time and adapting the configuration/characteristics of the
display accordingly. In this way the user always perceives the display as being calibrated independently of the viewing
angle. However, this method requires an expensive user tracking method (such as an infrared, ultrasound or vision
based head tracking device) and is not useful for multiple concurrent users.
This paper presents another solution: instead of tracking the user and dynamically changing the behavior of the display,
we develop calibration algorithms that have inherent robustness against change of viewing angle. This new method also
has the advantage that it is a very cheap solution that does not require additional hardware such as head tracking. In
addition it also works for multiple viewers.
Producing displays without pixel defects or repairing defective pixels is technically not possible at this moment. This paper presents a new approach to solve this problem: defects are made invisible for the user by using image processing algorithms based on characteristics of the human eye. The performance of this new algorithm has been evaluated using two different methods. First of all the theoretical response of the human eye was analyzed on a series of images and this before and after applying the defective pixel compensation algorithm. These results show that indeed it is possible to mask a defective pixel. A second method was to perform a psycho-visual test where users were asked whether or not a defective pixel could be perceived. The results of these user tests also confirm the value of the new algorithm. Our "defective pixel correction" algorithm can be implemented very efficiently and cost-effectively as pixel-dataprocessing algorithms inside the display in for instance an FPGA, a DSP or a microprocessor. The described techniques are also valid for both monochrome and color displays ranging from high-quality medical displays to consumer LCDTV
applications.
The electrical activity of the brain can be monitored using ElectroEncephaloGraphy (EEG). From the positions of the EEG electrodes, it is possible to localize focal brain activity. Thereby, the accuracy of the localization strongly depends on the accuracy with which the positions of the electrodes can be determined. In this work, we present an automatic, simple, and accurate scheme that detects EEG electrode markers from 3D MR data of the human head.
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