High-performance 3D median filter architecture for medical image despeckling

A high-sample rate 3D median filtering processor architecture is proposed, based on a novel 3D median filtering algorithm, that can reduce the computing complexity in comparison with the traditional bubble sorting algorithm. A 3 x 3 x 3 filter processor is implemented in VHDL, and the simulation verifies that the processor can process a 128 x 128 x 96 MRI image in 0.03 seconds while running at 50 MHz.

Comparison between laser scanning tomography and computerised image analysis of the optic disc

Aims - To study the interchangeability of the measurements of the optic disc topography obtained by one computerised image analyser and one confocal laser tomographic scanner. Methods - One eye of 28 patients with glaucoma or glaucoma suspects was studied. All cases had simultaneous stereoscopic disc photographs taken with the fundus camera Topcon TRC-SS and optic disc examination with the Heidelberg retina tomograph (HRT) during the same visit. The optic disc photographs were digitised and analysed with the Topcon ImageNet (TI) system. Three variables of the optic disc topography provided by the TI and the HRT were compared - cup volume (CV), rim area (RA), and cup area to disc area ratio (CA/DA). Results - The mean values of CV and RA provided by the TI (0.52 (SD 0.32) mm and 1.58 (0.39) mm , respectively) were greater (p <0.01) than the mean values of CV and RA determined by the HRT (0.32 (0.25) mm , and 1.33 (0.47) mm , respectively). The mean value of CA/DA provided by the TI (0.42 (0.14)) and the HRT (0.42 (0.18)) was similar (p = 0.93). Correlation coefficients between measurements obtained by the two methods ranged from 0.53 to 0.73. Conclusion - There was a significant discrepancy in the measurements of rim area and cup volume of the optic disc obtained by a computerised image analyser and a laser scanning tomograph.

Detection of changes of the optic disc in glaucomatous eyes:Clinical examination and image analysis with the Topcon Imagenet system

Purpose: This study was designed to evaluate the clinical agreement in the detection of optic disc changes and the ability of computerized image analysis to detect glaucomatous deterioration of the optic disc. Methods: Pairs of stereophotographs of 35 glaucomatous optic discs taken 5 years apart and of 5 glaucomatous discs photographed twice on the same day. Two glaucoma specialists examined the pairs of stereophotographs (35 cases and 5 controls) in a masked manner and judged whether the optic disc showed changes in the optic disc compatible with progression of glaucomatous damage. The stereophotographs of the five optic discs photographed twice on the same day (which by definition did not change) and of five cases judged to have deteriorated by both glaucoma specialists were analyzed by computerized image analysis with the Topcon ImageNet system. Intra- and inter-observer agreement in the detection of optic disc changes (evaluated using kappa statistic), and changes in the rim area to disc area ratio (evaluated using descriptive statistics and paired t-test). Results: Intra-observer agreement had a kappa value of 0.75 for observer 1 and 0.60 for the observer 2. Inter-observer agreement between the glaucoma specialists had a kappa value of 0.60. The image analyzer did not discriminate between controls and cases with clinically apparent glaucomatous change of the optic disc. Conclusion: Clinical agreement in detecting changes in the optic disc was moderate to substantial. Computerized image analysis with the Topcon ImageNet system appeared not to be useful in detecting glaucomatous changes of the optic disc.

Digital pathology and image analysis in tissue biomarker research

Digital pathology and the adoption of image analysis have grown rapidly in the last few years. This is largely due to the implementation of whole slide scanning, advances in software and computer processing capacity and the increasing importance of tissue-based research for biomarker discovery and stratified medicine. This review sets out the key application areas for digital pathology and image analysis, with a particular focus on research and biomarker discovery. A variety of image analysis applications are reviewed including nuclear morphometry and tissue architecture analysis, but with emphasis on immunohistochemistry and fluorescence analysis of tissue biomarkers. Digital pathology and image analysis have important roles across the drug/companion diagnostic development pipeline including biobanking, molecular pathology, tissue microarray analysis, molecular profiling of tissue and these important developments are reviewed. Underpinning all of these important developments is the need for high quality tissue samples and the impact of pre-analytical variables on tissue research is discussed. This requirement is combined with practical advice on setting up and running a digital pathology laboratory. Finally, we discuss the need to integrate digital image analysis data with epidemiological, clinical and genomic data in order to fully understand the relationship between genotype and phenotype and to drive discovery and the delivery of personalized medicine.