Claes Lundström

Local Histograms for Design of Transfer Functions in Direct Volume Rendering

Direct volume rendering (DVR) is of increasing diagnostic value in the analysis of data sets captured using the latest medical imaging modalities. The deployment of DVR in everyday clinical work, however, has so far been limited. One contributing factor is that current transfer function (TF) models can encode only a small fraction of the users domain knowledge. In this paper, we use histograms of local neighborhoods to capture tissue characteristics. This allows domain knowledge on spatial relations in the data set to be integrated into the TF. As a first example, we introduce partial range histograms in an automatic tissue detection scheme and present its effectiveness in a clinical evaluation. We then use local histogram analysis to perform a classification where the tissue-type certainty is treated as a second TF dimension. The result is an enhanced rendering where tissues with overlapping intensity ranges can be discerned without requiring the user to explicitly define a complex, multidimensional TF

Full Body Virtual Autopsies using a State-of-the-art Volume Rendering Pipeline

This paper presents a procedure for virtual autopsies based on interactive 3D visualizations of large scale, high resolution data from CT-scans of human cadavers. The procedure is described using examples from forensic medicine and the added value and future potential of virtual autopsies is shown from a medical and forensic perspective. Based on the technical demands of the procedure state-of-the-art volume rendering techniques are applied and refined to enable real-time, full body virtual autopsies involving gigabyte sized data on standard GPUs. The techniques applied include transfer function based data reduction using level-of-detail selection and multi-resolution rendering techniques. The paper also describes a data management component for large, out-of-core data sets and an extension to the GPU-based raycaster for efficient dual TF rendering. Detailed benchmarks of the pipeline are presented using data sets from forensic cases

Multiresolution interblock interpolation in direct volume rendering

We present a direct interblock interpolation technique that enables direct volume rendering of blocked, multiresolution volumes. The proposed method smoothly interpolates between blocks of arbitrary block-wise level-of-detail (LOD) without sample replication or padding. This permits extreme changes in resolution across block boundaries and removes the interblock dependency for the LOD creation process. In addition the full data reduction from the LOD selection can be maintained throughout the rendering pipeline. Our rendering pipeline employs a flat block subdivision followed by a transfer function based adaptive LOD scheme. We demonstrate the effectiveness of our method by rendering volumes of the order of gigabytes using consumer graphics cards on desktop PC systems.

Extending and simplifying transfer function design in medical volume rendering using local histograms

Direct Volume Rendering (DVR) is known to be of diagnostic value in the analysis of medical data sets. However, its deployment in everyday clinical use has so far been limited. Two major challenges are that the current methods for Transfer Function (TF) construction are too complex and that the tissue separation abilities of the TF need to be extended. In this paper we propose the use of histogram analysis in local neighborhoods to address both these conflicting problems. To reduce TF construction difficulty, we introduce Partial Range Histograms in an automatic tissue detection scheme, which in connection with Adaptive Trapezoids enable efficient TF design. To separate tissues with overlapping intensity ranges, we propose a fuzzy classification based on local histograms as a second TF dimension. This increases the power of the TF, while retaining intuitive presentation and interaction.

Implementation of large-scale routine diagnostics using whole slide imaging in Sweden: Digital pathology experiences 2006-2013.

Recent technological advances have improved the whole slide imaging (WSI) scanner quality and reduced the cost of storage, thereby enabling the deployment of digital pathology for routine diagnostics. In this paper we present the experiences from two Swedish sites having deployed routine large-scale WSI for primary review. At Kalmar County Hospital, the digitization process started in 2006 to reduce the time spent at the microscope in order to improve the ergonomics. Since 2008, more than 500,000 glass slides have been scanned in the routine operations of Kalmar and the neighboring Linköping University Hospital. All glass slides are digitally scanned yet they are also physically delivered to the consulting pathologist who can choose to review the slides on screen, in the microscope, or both. The digital operations include regular remote case reporting by a few hospital pathologists, as well as around 150 cases per week where primary review is outsourced to a private clinic. To investigate how the pathologists choose to use the digital slides, a web-based questionnaire was designed and sent out to the pathologists in Kalmar and Linköping. The responses showed that almost all pathologists think that ergonomics have improved and that image quality was sufficient for most histopathologic diagnostic work. 38 ± 28% of the cases were diagnosed digitally, but the survey also revealed that the pathologists commonly switch back and forth between digital and conventional microscopy within the same case. The fact that two full-scale digital systems have been implemented and that a large portion of the primary reporting is voluntarily performed digitally shows that large-scale digitization is possible today.

Multi-Touch Table System for Medical Visualization: Application to Orthopedic Surgery Planning

Medical imaging plays a central role in a vast range of healthcare practices. The usefulness of 3D visualizations has been demonstrated for many types of treatment planning. Nevertheless, full access to 3D renderings outside of the radiology department is still scarce even for many image-centric specialties. Our work stems from the hypothesis that this under-utilization is partly due to existing visualization systems not taking the prerequisites of this application domain fully into account. We have developed a medical visualization table intended to better fit the clinical reality. The overall design goals were two-fold: similarity to a real physical situation and a very low learning threshold. This paper describes the development of the visualization table with focus on key design decisions. The developed features include two novel interaction components for touch tables. A user study including five orthopedic surgeons demonstrates that the system is appropriate and useful for this application domain.

State-of-the-art of visualization in post-mortem imaging

Lundström C, Persson A, Ross S, Ljung P, Lindholm S, Gyllensvärd F, Ynnerman A. State‐of‐the‐art of visualization in post‐mortem imaging. APMIS 2012; 120: 316–26.

The α-histogram: using spatial coherence to enhance histograms and transfer function design

The high complexity of Transfer Function (TF) design is a major obstacle to widespread routine use of Direct Volume Rendering, particularly in the case of medical imaging. Both manual and automatic TF design schemes would benefit greatly from a fast and simple method for detection of tissue value ranges. To this end, we introduce the a-histogram, an enhancement that amplifies ranges corresponding to spatially coherent materials. The properties of the a-histogram have been explored for synthetic data sets and then successfully used to detect vessels in 20 Magnetic Resonance angiographies, proving the potential of this approach as a fast and simple technique for histogram enhancement in general and for TF construction in particular.

Fully automatic measurements of axial vertebral rotation for assessment of spinal deformity in idiopathic scoliosis

Reliable measurements of spinal deformities in idiopathic scoliosis are vital, since they are used for assessing the degree of scoliosis, deciding upon treatment and monitoring the progression of the disease. However, commonly used two dimensional methods (e.g. the Cobb angle) do not fully capture the three dimensional deformity at hand in scoliosis, of which axial vertebral rotation (AVR) is considered to be of great importance. There are manual methods for measuring the AVR, but they are often time-consuming and related with a high intra- and inter-observer variability. In this paper, we present a fully automatic method for estimating the AVR in images from computed tomography. The proposed method is evaluated on four scoliotic patients with 17 vertebrae each and compared with manual measurements performed by three observers using the standard method by Aaro-Dahlborn. The comparison shows that the difference in measured AVR between automatic and manual measurements are on the same level as the inter-observer difference. This is further supported by a high intraclass correlation coefficient (0.971-0.979), obtained when comparing the automatic measurements with the manual measurements of each observer. Hence, the provided results and the computational performance, only requiring approximately 10 to 15 s for processing an entire volume, demonstrate the potential clinical value of the proposed method.

Transfer function based adaptive decompression for volume rendering of large medical data sets

The size of standard volumetric data sets in medical imaging is rapidly increasing causing severe performance limitations in direct volume rendering pipelines. The methods presented in this paper exploit the medical knowledge embedded in the transfer function to reduce the required bandwidth in the pipeline. Typically, medical transfer functions cause large subsets of the volume to give little or no contribution to the rendered image. Thus, parts of the volume can be represented at low resolution while retaining overall visual quality. This paper introduces the use of transfer functions at decompression time to guide a level-of-detail selection scheme. The method may be used in combination with traditional lossy or lossless compression schemes. We base our current implementation on a multi-resolution data representation using compressed wavelet transformed blocks. The presented results using the adaptive decompression demonstrate a significant reduction in the required amount of data while maintaining rendering quality. Even though the focus of this paper is medical imaging, the results are applicable to volume rendering in many other domains.