Pathological and Test Cases For Reeb Analysis

After two decades in computational topology, it is clearly a computationally challenging area. Not only do we have the usual algorithmic and programming difficulties with establishing correctness, we also have a class of problems that are mathematically complex and notationally fragile. Effective development and deployment therefore requires an additional step - construction or selection of suitable test cases. Since we cannot test all possible inputs, our selection of test cases expresses our understanding of the task and of the problems involved. Moreover, the scale of the data sets we work with is such that, no matter how unlikely the behaviour mathematically, it is nearly guaranteed to occur at scale in every run. The test cases we choose are therefore tightly coupled with mathematically pathological cases, and need to be developed using the skills expressed most obviously in the constructing mathematical counterexamples. This paper is therefore a first attempt at reporting, classifying and analysing test cases previously used in computational topology, and the expression of a philosophy of how to test topological code

Learning from Failure – An Important Step in Innovation

There is a reluctance to publish “negative” data in many fields. However, there is so much to be learned from what did not work! Failure can be an important step in innovation. Health professional educators around the world strive to deliver effective SP-based interventions for their learners by leveraging on the strengths and opportunities whilst mitigating any challenges they face in their local context. The pandemic has created unprecedented pressure to “try something new” as we navigate the prevailing safe management measures and restrictions imposed at various levels (government, organizational, personal preference). Whilst many adaptations result in effective interventions, sometimes we learn more from the innovations that did not go quite as planned. The ability to see failure as a stepping-stone to success is a quality we should celebrate. The Association of SP Educators (ASPE) International Committee is charged with building member networks, identifying cultural differences in context and approach to SP simulation, and outlining needs of international SP programs. In this spirit, SP educators from the ASPE International Committee, representing several countries, will present examples of times they learned a great deal through trial and error. They will offer suggestions for adaptations of SP practice and describe lessons learned with reference to the ASPE Standards of Best Practice and with particular emphasis on ethical components, including safe work practices. Workshop Objectives Describe ways in which the COVID-19 pandemic has been a driver for change Explore examples of innovations and adaptations to practice Reflect on the value of failure as a steppingstone in innovation Planned Format Through a series of micro presentations interspersed with large and small group discussions, we will hear examples of lessons learned through innovation during a time of unprecedented change

Real-Time Molecular Diagnosis of Tumors Using Atmospheric Pressure Infrared Matrix-Assisted Laser Desorption-Ionization Mass Spectrometry

International audienceTissue diagnosis is critical in the clinical management of cancer patients. Mass Spectrometry (MS) has long been of interest for discriminating cells using tissue sections of patient biopsies. However, the main challenge arises in the context of intraoperative tissue analyses, where the MS instrument must operate within a surgical environment. To date, only the Intelligent Knife (iKnife) system allowed real-time monitoring during surgery by collecting aerosol released during tissue excision with an electric scalpel or bipolar forceps [1]. Recently we have demonstrated that in vivo real-time analyses can be less invasive using laser ablation. In our prototype, a fibered IR Optical Parametric Oscillator (OPO) is tuned at 2.94 µm to excite the most intense vibrational band (O-H stretching mode) of water molecules found abundantly in all biological tissues. Water acts as a natural endogenous Matrix-Assisted Laser Desorption-Ionization (MALDI) matrix leading to the production of ions that can be transported over a few meters to a MS instrument for analysis without requiring further post-ionization handling. The molecular patterns (metabolites, lipids and proteins) thus retrieved are specific to cell phenotypes and benign versus cancer regions can easily be differentiated [2]. We present the first assessment of our prototype in a veterinary surgery room [3]. For this purpose, a series of benchmark studies have been initiated with the aim of building up an extensive databank able to relate distinct molecular profiles to a specific type of pathology, namely the dog sarcoma. These studies are accompanied by the development of a real-time query interface. Classification models based on tumor grade (cancer/normal/necrotic) and cancer subtype developed in this work showed a minimum of ~98% correct classification when put to use. The system demonstrated clear-cut margin detection capabilities that have been validated in correlation with histology. Finally, this instrument enables real-time diagnostics by the immediate interrogation of classification models established ahead of time

Enhancing 3D Mesh Topological Skeletons with Discrete Contour Constrictions

International audienceThis paper describes a unified and fully automatic algorithm for Reeb graph construction and simplification as well as constriction approximation on triangulated surfaces. The key idea of the algorithm is that discrete contours - curves carried by the edges of the mesh and approximating the continuous contours of a mapping function - encode both topological and geometrical shape characteristics. Therefore, a new concise shape representation, enhanced topological skeletons, is proposed, encoding contours' topological and geometrical evolution. Firstly, mesh feature points are computed. Then they are used as geodesic origins for the computation of an invariant mapping function that reveals the shape most significant features. Secondly, for each vertex in the mesh, its discrete contour is computed. As the set of discrete contours recovers the whole surface, each of them can be analyzed, both to detect topological changes and constrictions. Constriction approximations enable Reeb graphs refinement into more visually meaningful skeletons, that we refer as enhanced topological skeletons. Extensive experiments showed that, without preprocessing stage, proposed algorithms are fast in practice, affine-invariant and robust to a variety of surface degradations (surface noise, mesh sampling and model pose variations). These properties make enhanced topological skeletons interesting shape abstractions for many computer graphics applications