Acquiring experience in pathology predominantly from what you see, not from what you read: the HIPON e-learning platform

It is indisputable that nowadays one of the hardest and most important tasks in medicine and especially in medical education, is the conversion of the extensive amount of available data, into medical experience, after a proper analysis. A project under the title "ICT (Information and Communication Technology) eModules on HistoPathology: a useful online tool for students, researchers and professionals - HIPON", co-financed by the Lifelong Learning Program of the Education, Audiovisual and Culture Executive Agency (EACEA), The Commission of the European Union, has been launched at the beginning of 2013. HIPON's purpose is not to provide just another pathology website atlas, but to convey professional experience and thinking in pathology. HIPON has resulted in a well-structured and user-friendly, open resource, multi-language, e-learning platform which, taking advantage of modern image technology, offers medical students, researchers, and professionals a valuable teaching instrument so that they can acquire professional experience in pathology. The mid-term report of HIPON has been favorably evaluated by the EACEA experts who appreciated the potential of our teaching tool in providing the opportunity and the means to acquire medical experience. Through the use of virtual slides, educative videos and microscopic, high resolution, marked images accompanied by relevant questions and answers, HIPON project aims to make end-users able to think as experienced pathologists and become highly efficient in correlating pathologic data with other clinical-laboratory information

Mitral valve flattening and parameter mapping for patient-specific valve diagnosis

Purpose!#!Intensive planning and analysis from echocardiography are a crucial step before reconstructive surgeries are applied to malfunctioning mitral valves. Volume visualizations of echocardiographic data are often used in clinical routine. However, they lack a clear visualization of the crucial factors for decision making.!##!Methods!#!We build upon patient-specific mitral valve surface models segmented from echocardiography that represent the valve's geometry, but suffer from self-occlusions due to complex 3D shape. We transfer these to 2D maps by unfolding their geometry, resulting in a novel 2D representation that maintains anatomical resemblance to the 3D geometry. It can be visualized together with color mappings and presented to physicians to diagnose the pathology in one gaze without the need for further scene interaction. Furthermore, it facilitates the computation of a Pathology Score, which can be used for diagnosis support.!##!Results!#!Quality and effectiveness of the proposed methods were evaluated through a user survey conducted with domain experts. We assessed pathology detection accuracy using 3D valve models in comparison with the novel visualizations. Classification accuracy increased by 5.3% across all tested valves and by 10.0% for prolapsed valves. Further, the participants' understanding of the relation between 3D and 2D views was evaluated. The Pathology Score is found to have potential to support discriminating pathologic valves from normal valves.!##!Conclusions!#!In summary, our survey shows that pathology detection can be improved in comparison with simple 3D surface visualizations of the mitral valve. The correspondence between the 2D and 3D representations is comprehensible, and color-coded pathophysiological magnitudes further support the clinical assessment