Tom Kimpe is Vice President Technology & Innovation of Barco’s Healthcare Division. He is coordinating an international team of engineers developing tomorrow’s innovative visualization products that will improve healthcare.
Tom holds an engineering degree in computer science and a PhD in electrical engineering from University of Ghent, Belgium. In 2010 he finalized a Master in Business Administration (MBA) at the Vlerick Management School.
Since 2001 Tom has been working in Barco's Healthcare Division. He has taken several positions including development engineer, project manager, innovation manager, VP of Technology and Innovation and Chief Technology Officer of Barco's Healthcare Division. Already for several years, Tom is coordinating all research and innovation activities of Barco's Healthcare Division and is steering an international team of engineers in USA, Belgium and Italy. His main topics of expertise are (medical) display technology, image and signal processing, image quality modelling, network technology and medical regulatory aspects. Tom is author and co-author of tens of scientific publications in conference proceedings and journals. He also is inventor of multiple patents.
Tom holds an engineering degree in computer science and a PhD in electrical engineering from University of Ghent, Belgium. In 2010 he finalized a Master in Business Administration (MBA) at the Vlerick Management School.
Since 2001 Tom has been working in Barco's Healthcare Division. He has taken several positions including development engineer, project manager, innovation manager, VP of Technology and Innovation and Chief Technology Officer of Barco's Healthcare Division. Already for several years, Tom is coordinating all research and innovation activities of Barco's Healthcare Division and is steering an international team of engineers in USA, Belgium and Italy. His main topics of expertise are (medical) display technology, image and signal processing, image quality modelling, network technology and medical regulatory aspects. Tom is author and co-author of tens of scientific publications in conference proceedings and journals. He also is inventor of multiple patents.
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The past few years digital pathology has been widely adopted. The display system is a crucial component in the overall digital pathology system, since pathologists decide based upon images visualized on the display. Quality of the display can influence clinical performance, but also workflow efficiency and ergonomics.
Performance of radiology display systems has been extensively studied, and this resulted into standardization and clear requirements and guidelines. Digital pathology images and viewing conditions are very different compared to radiology. Fewer effort has gone in understanding what makes a digital pathology display fit for use, and there is no consensus yet in the digital pathology community about ideal specifications for digital pathology displays.
This paper studies specific characteristics of digital pathology display systems, such as luminance, contrast and resolution. Effects of these characteristics on visibility of relevant pathological features is described, and recommendations are made for clinically meaningful levels of luminance, contrast and resolution.
We previously introduced VCT-Derma, a pipeline for dermatological Virtual Clinical Trials (VCTs) including detailed and flexible models of human skin and lesions, which represent the patient in the entire dermatoscopy-based diagnostic process. However, those initial models of skin and lesions did not properly account for tissue colors.
Our new skin model accounts for tissue color appearance by incorporating chromophores (e.g., melanin, blood) into the tissue model, and simulating the optical properties of the various skin layers. The physical properties of the skin and lesion were selected from clinically plausible values. The model and simulated dermatoscope images were created in open modelling software, assuming a linear camera model. We have assumed ambient white lighting, with a 6mm distance to the camera.
Our model of color appearance was characterised by comparing the brightness of the lesion to its depth. The brightness of the lesion is compared through the variability of the mean gray values of a cropped region around the lesion. We compare two skin models, one without extensive chromophore content and one with. Our preliminary evaluation of increasing chromophore content shows promise based on the results presented here. Further refinement and validation of the model is ongoing.
Development and evaluation of a 3D model observer with nonlinear spatiotemporal contrast sensitivity
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