Chiara Eva Catalano’s research while affiliated with Istituto di Matematica Applicata e Tecnologie Informatiche, Italian National Research Council and other places

Embeddings are fundamental resources often reused for building intelligent systems in the biomedical context. As a result, evaluating the quality of previously trained embeddings and ensuring they cover the desired information is critical for the success of applications. This paper proposes a new evaluation methodology to test the coverage of embeddings against a targetted domain of interest. It defines measures to assess the terminology, similarity, and analogy coverage, which are core aspects of the embeddings. Then, it discusses the experimentation carried out on existing biomedical embeddings in the specific context of pulmonary diseases. The proposed methodology and measures are general and may be applied to any application domain.

Thanks to continuous efforts towards 3D digitisation in the Cultural Heritage (CH) domain, we have experienced increasing interest in mathematical methods and computer graphics tools that can concretely support archaeological research and extend curatorial systems, so that the potential of digital data can be exploited beyond the mere rendering and visualisation of artefacts. This trend calls for robust and supportive methods for the analysis, characterisation and documentation of digital artefacts. Many are the applications that can assist the work of the professionals in the field of artistic/archaeological research, and curation: hypothesis formulation and interpretation, indexing and retrieval of content, and exploration of collections along new and dynamic dimensions. In this work, we present a variety of computational approaches tailored to CH applications, and archaeology especially, tested in real use cases by practitioners of the field, spanning from shape analysis to indexing of 3D assets.Keywords3D model characterisationSimilarity reasoningSemantic annotationComputational archeology

The Artistic goods represent a priceless asset of our cultural patrimony since they play a crucial role in defining and understanding the identity of communities. Nevertheless, they are not always adequately protected against possible dangers and hazards or the effects of time. In these last decades, the new technologies - such as the digital control, the 3D reconstructions etc. - have experienced great developments even in their application to the art collections, increasing the monitoring activities, the safety checking, and their interface with the community. The ARCO 2020 Conference collected contributions from different areas for the preservation, the enhancement, and the protection of the art goods exhibited in the Museums. This volume collects the proceeding of the sessions about Design and Museum Design, Digital Heritage, Historical Research and Posters of the ARCO 2020 international conference which took place on 21-23 September 2020 in Florence, Italy, at the Dipartimento di Architettura (DiDA).

In this paper, we will explore the theme of the documentation of 3D cultural heritage assets, not only as entire artefacts but also including the interesting features of the object from an archaeological perspective. Indeed, the goal is supporting archaeological research and curation, providing a different approach to enrich the documentation of digital resources and their components with corresponding measurements, combining semantic and geometric techniques. A documentation scheme based on CIDOC, where measurements on digital data have been included extending CIDOC CRMdig, is discussed. To annotate accurately the components and features of the artefacts, a controlled vocabulary named Cultural Heritage Artefact Partonomy (CHAP) has been defined and integrated into the scheme as a SKOS taxonomy to showcase the proposed methodology. CHAP concerns Coroplastic, which is the study of ancient terracotta figurines and in particular the Cypriot production. Two case studies have been considered: the terracotta statues from the port of Salamis and the small clay statuettes from the Ayia Irini sanctuary. Focussing both on the artefacts and their digital counterparts, the proposed methodology supports effectively typical operations within digital libraries and repositories (e.g. search, part-based annotation), and more specific objectives such as the archaeological interpretation and digitally assisted classification, as proved in a real archaeological scenario. The proposed approach is general and applies to different contexts, since it is able to support any archaeological research where the goal is an extensive digital documentation of tangible findings including quantitative attributes.

The objective of this work is the design of a technological platform for remote monitoring of patients with Chronic Obstructive Pulmonary Disease (COPD). The concept of the framework is a breakthrough in the state of medical, scientific and technological art, aimed at engaging patients in the treatment plan and supporting interaction with healthcare professionals. The proposed platform is able to support a new paradigm for the management of patients with COPD, by integrating clinical data and parameters monitored in daily life using Artificial Intelligence algorithms. Therefore, the doctor is provided with a dynamic picture of the disease and its impact on lifestyle and vice versa, and can thus plan more personalized diagnostics, therapeutics, and social interventions. This strategy allows for a more effective organization of access to outpatient care and therefore a reduction of emergencies and hospitalizations because exacerbations of the disease can be better prevented and monitored. Hence, it can result in improvements in patients' quality of life and lower costs for the healthcare system.

In this work we introduce a method for the recognition, modelling and interactive manipulation of graphical motifs, symbols or artistic elements that are represented by a composition of plane curves. Our method bases on Hough transform (HT) concepts, in particular on its generalisation to algebraic curves. We recognise complex curves and their compositions starting from images or point clouds, we represent them in implicit or parametric form, and their parameters are calculated together with their relationships. Besides the recognition of curves and modelling by algebraic equations, we propose a visualisation and manipulation tool developed on a multi-touch table. The objective of this application is to support an interactive manipulation of any geometric motifs or symbols with or without imposing the constraints derived from the identified relations among the curve parameters. Finally, we validate the proposed method showing its application to three detailed case studies, which differ in type and creation mode.

Background: Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses. Results: In this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences. Conclusions: We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.

The GRAVITATE project is developing techniques that bring together geometric and semantic data analysis to provide a new and more effective method of re-associating, reassembling or reunifying cultural objects that have been broken or dispersed over time. The project is driven by the needs of archaeological institutes, and the techniques are exemplified by their application to a collection of several hundred 3D-scanned fragments of large-scale terracotta statues from Salamis, Cyprus. The integration of geometrical feature extraction and matching with semantic annotation and matching into a single decision support platform will lead to more accurate reconstructions of artefacts and greater insights into history. In this paper we describe the project and its objectives, then we describe the progress made to date towards achieving those objectives: describing the datasets, requirements and analysing the state of the art. We follow this with an overview of the architecture of the integrated decision support platform and the first realisation of the user dashboard. The paper concludes with a description of the continuing work being undertaken to deliver a workable system to cultural heritage curators and researchers.

In the digital era, patient-specific 3D models (3D-PSMs) are becoming increasingly relevant in computerassisted diagnosis, surgery training on digital models, or implant design. While advanced imaging and reconstruction techniques can create accurate and detailed 3D models of patients’ anatomy, software tools that are able to fully exploit the potential of 3D-PSMs are still far from being satisfactory. In particular, there is still a lack of integrated approaches for extracting, coding, sharing and retrieving medically relevant information from 3D-PSMs and use it concretely as a support to diagnosis and treatment. In this article, we propose the SemAnatomy3D framework, which demonstrates how the ontology-driven annotation of 3D-PSMs and of their anatomically relevant features (parts of relevance) can assist clinicians to document more effectively pathologies and their evolution. We exemplify the idea in the context of the diagnosis of rheumatoid arthritis of the hand district, and show how feature extraction tools and semantic 3D annotation can provide a rich characterization of anatomical landmarks (e.g., articular facets, prominent features, ligament attachments) and pathological markers (erosions, bone loss). The core contributions are an ontology-driven part-based annotation method for the 3D-PSMs and a novel automatic localization of erosion and quantification of the OMERACT RAMRIS erosion score. Finally, our results have been compared against a medical ground truth.

In GRAVITATE, two disparate specialities will come together in one working platform for the archaeologist: the fields of shape analysis, and of metadata search. These fields are relatively disjoint at the moment, and the research and development challenge of GRAVITATE is precisely to merge them for our chosen tasks. As shown in chapter 7 the small amount of literature that already attempts join 3D geometry and semantics is not related to the cultural heritage domain. Therefore, after the project is done, there should be a clear ‘before-GRAVITATE’ and ‘after-GRAVITATE’ split in how these two aspects of a cultural heritage artefact are treated. This state of the art report (SOTA) is ‘before-GRAVITATE’. Shape analysis and metadata description are described separately, as currently in the literature and we end the report with common recommendations in chapter 8 on possible or plausible cross-connections that suggest themselves. These considerations will be refined for the Roadmap for Research deliverable. Within the project, a jargon is developing in which ‘geometry’ stands for the physical properties of an artefact (not only its shape, but also its colour and material) and ‘metadata’ is used as a general shorthand for the semantic description of the provenance, location, ownership, classification, use etc. of the artefact. As we proceed in the project, we will find a need to refine those broad divisions, and find intermediate classes (such as a semantic description of certain colour patterns), but for now the terminology is convenient – not least because it highlights the interesting area where both aspects meet. On the ‘geometry’ side, the GRAVITATE partners are UVA, Technion, CNR/IMATI; on the metadata side, IT Innovation, British Museum and Cyprus Institute; the latter two of course also playing the role of internal users, and representatives of the Cultural Heritage (CH) data and target user’s group. CNR/IMATI’s experience in shape analysis and similarity will be an important bridge between the two worlds for geometry and metadata. The authorship and styles of this SOTA reflect these specialisms: the first part (chapters 3 and 4) purely by the geometry partners (mostly IMATI and UVA), the second part (chapters 5 and 6) by the metadata partners, especially IT Innovation while the joint overview on 3D geometry and semantics is mainly by IT Innovation and IMATI. The common section on Perspectives was written with the contribution of all.