Sviluppo di funzionalità di augmented reality per computer assisted surgery

Negli ultimi anni, l'augmented reality -AR- ha aperto una finestra su un mondo di possibilità, che trovano spazio in tantissimi campi, anche molto diversi tra loro. Uno di questi è la chirurgia assistita dal computer (computer assisted surgery -CAS-). In questo lavoro, verrà mostrata un'interessante applicazione dell'AR in questo ambito, che consiste nel mixare, in modo coerente e in tempo reale, modelli virtuali 3D di parti anatomiche di un paziente, ottenuti da immagini TAC o RM, con immagini dal vivo di esso, acquisite per mezzo di telecamere. Il dispositivo utilizzato è un visore 3D dotato di telecamere, leggero e portatile (nonché economico), che un chirurgo può indossare, in fase pre-operatoria, per visualizzare il risultato degli esami radiologici, direttamente sul paziente e così pianificare meglio l'intervento che si sta accingendo a compiere. Le varie fasi che portano alla fusione delle immagini reali e virtuali verranno analizzate nel dettaglio, sia nei loro aspetti teorici che nei loro aspetti pratici: partiremo con le problematiche relative alla calibrazione, che ci porteranno a trovare un modello per descrivere analiticamente una telecamera, mediante alcuni parametri propri di essa e altri propri del modo di inquadrare la scena; continueremo occupandoci di aspetti di computer vision, (in particolare di pattern detection), al fine di localizzare alcuni pattern noti in precedenza, che, grazie alle loro caratteristiche, sono in grado di fornire informazioni sulla loro posizione/orientazione rispetto alle telecamere, creando così una relazione mondo-telecamera che si aggiorna in tempo reale; per concludere, tramite le informazioni ottenute in precedenza modelleremo due telecamere virtuali che abbiano lo stesso comportamento di quelle reali, istante per istante, in modo tale da consentire un perfetto matching real-time delle due scene inquadrate (quella reale e quella virtuale, costituita dall'immagine radiologica). L'analisi dei risultati sperimentali mostrerà un ottimo comportamento del sistema in quanto ad accuratezza e latenza, che fanno sì che il mix di elementi reali e virtuali risulti verosimile e dunque ben usufruibile

A flexible algorithm for detecting challenging moving objects in real-time within IR video sequences

Real-time detecting moving objects in infrared video sequences may be particularly challenging because of the characteristics of the objects, such as their size, contrast, velocity and trajectory. Many proposed algorithms achieve good performances but only in the presence of some specific kinds of objects, or by neglecting the computational time, becoming unsuitable for real-time applications. To obtain more flexibility in different situations, we developed an algorithm capable of successfully dealing with small and large objects, slow and fast objects, even if subjected to unusual movements, and poorly-contrasted objects. The algorithm is also capable to handle the contemporary presence of multiple objects within the scene and to work in real-time even using cheap hardware. The implemented strategy is based on a fast but accurate background estimation and rejection, performed pixel by pixel and updated frame by frame, which is robust to possible background intensity changes and to noise. A control routine prevents the estimation from being biased by the transit of moving objects, while two noise-adaptive thresholding stages, respectively, drive the estimation control and allow extracting moving objects after the background removal, leading to the desired detection map. For each step, attention has been paid to develop computationally light solution to achieve the real-time requirement. The algorithm has been tested on a database of infrared video sequences, obtaining promising results against different kinds of challenging moving objects and outperforming other commonly adopted solutions. Its effectiveness in terms of detection performance, flexibility and computational time make the algorithm particularly suitable for real-time applications such as intrusion monitoring, activity control and detection of approaching objects, which are fundamental task in the emerging research area of Smart City

Utilizzo di Immagini Acquisite da Drone Aereo per la Ricostruzione Tridimensionale Realistica di un'Area di Interesse in Tempo Reale

Tridimensional reconstruction of areas and objects of interest from images acquired from aerial drones plays a key role in numerous fields, from the less critical, like urban planning and archeological area survey, to the most critical, like natural disaster monitoring, and search & rescue. Many techniques proposed to deal with this issue require expensive instrumentation or use computationally costly algorithm or need some a priori information that are not always available. Thus, they are not suitable for certain applications or in some specific situations. In order to overcome these limitations, we designed a technique that allows automatically creating 3D models in real-time using only a couple of images of the scene one is interested in, acquired with a cheap compact camera mounted on the drone, without the needing for any additional information. The proposed technique outputs dense true-color 3D models, which give the impression to the user to be physically present within the scene. Tested for monitoring the progress of the works in a construction site, the technique has been capable to create realistic and easy-to-interpret 3D models of areas and objects in less than 1 second and with a sufficient accuracy to permit large-scale surveys

Determining the Difficulties of Students With Dyslexia via Virtual Reality and Artificial Intelligence: An Exploratory Analysis

Learning disorders are neurological conditions that affect the brain's ability to interconnect communication areas. Dyslexic students experience problems with reading, memorizing, and exposing concepts; however the magnitude of these can be mitigated through both therapies and the creation of compensatory mechanisms. Several efforts have been made to mitigate these issues, leading to the creation of digital resources for students with specific learning disorders attending primary and secondary education levels. Conversely, a standard approach is still missed in higher education. The VRAIlexia project has been created to tackle this issue by proposing two different tools: a mobile application integrating virtual reality (VR) to collect data quickly and easily, and an artificial intelligencebased software (AI) to analyze the collected data for customizing the supporting methodology for each student. The first one has been created and is being distributed among dyslexic students in Higher Education Institutions, for the conduction of specific psychological and psychometric tests. The second tool applies specific artificial intelligence algorithms to the data gathered via the application and other surveys. These AI techniques have allowed us to identify the most relevant difficulties faced by the students' cohort. Our different models have obtained around 90\% mean accuracy for predicting the support tools and learning strategies.Comment: 7 pages, 5 figures, 3 tables, MetroXRAINE 2022 Conference, VRAILEXIA european projec

A VR Serious Game to Increase Empathy towards Students with Phonological Dyslexia

Dyslexia is a neurodevelopmental disorder that is estimated to affect about 5-10% of the population. In particular, phonological dyslexia causes problems in connecting the sounds of words with their written forms. This results in difficulties such as slow reading speed, inaccurate reading, and difficulty decoding unfamiliar words. Moreover, dyslexia can also be a challenging and frustrating experience for students as they may feel misunderstood or stigmatized by their peers or educators. For these reasons, the use of compensatory tools and strategies is of crucial importance for dyslexic students to have the same opportunities as non-dyslexic ones. However, generally, people underestimate the problem and are not aware of the importance of support methodologies. In the light of this, the main purpose of this paper is to propose a virtual reality (VR) serious game through which teachers, students and, in general, non-dyslexic people could understand which are some of the issues of student with dyslexia and the fundamental utility of offering support to them. In the game, players must create a potion by following a recipe written in an alphabet that is specifically designed to replicate the reading difficulties experienced by individuals with dyslexia. The task must be solved first without any help and then by receiving supporting tools and strategies with the idea that the player can put himself in the place of the dyslexic person and understand the real need for support methodologies.Comment: 5 pages, 5 figures, MetroXRAINE 202

Crystal Structure of the C-type Lectin-like Domain from the Human Hematopoietic Cell Receptor CD69

CD69, one of the earliest specific antigens acquired during lymphoid activation, acts as a signal-transducing receptor involved in cellular activation events, including proliferation and induction of specific genes. CD69 belongs to a family of receptors that modulate the immune response and whose genes are clustered in the natural killer (NK) gene complex. The extracellular portion of these receptors represent a subfamily of C-type lectin-like domains (CTLDs), which are divergent from true C-type lectins and are referred to as NK-cell domains (NKDs). We have determined the three-dimensional structure of human CD69 NKD in two different crystal forms. CD69 NKD adopts the canonical CTLD fold but lacks the features involved in Ca(2+) and carbohydrate binding by C-type lectins. CD69 NKD dimerizes noncovalently, both in solution and in crystalline state. The dimer interface consists of a hydrophobic, loosely packed core, surrounded by polar interactions, including an interdomain beta sheet. The intersubunit core shows certain structural plasticity that may facilitate conformational rearrangements for binding to ligands. The surface equivalent to the binding site of other members of the CTLD superfamily reveals a hydrophobic patch surrounded by conserved charged residues that probably constitutes the CD69 ligand-binding site.Fil: Llera, Andrea Sabina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; ArgentinaFil: Viedma, Fernando. Universidad Autónoma de Madrid; EspañaFil: Sánchez Madrid, Francisco. Universidad Autónoma de Madrid; EspañaFil: Tormo, José. Universidad Autónoma de Madrid; Españ

Opsonin-deficient nucleoproteic corona endows unPEGylated liposomes with stealth properties in vivo

For several decades, surface grafted polyethylene glycol (PEG) has been a go-to strategy for preserving the synthetic identity of liposomes in physiological milieu and preventing clearance by immune cells. However, the limited clinical translation of PEGylated liposomes is mainly due to the protein corona formation and the subsequent modification of liposomes’ synthetic identity, which affects their interactions with immune cells and blood residency. Here we exploit the electric charge of DNA to generate unPEGylated liposome/DNA complexes that, upon exposure to human plasma, gets covered with an opsonin-deficient protein corona. The final product of the synthetic process is a biomimetic nanoparticle type covered by a proteonucleotidic corona, or “proteoDNAsome”, which maintains its synthetic identity in vivo and is able to slip past the immune system more efficiently than PEGylated liposomes. Accumulation of proteoDNAsomes in the spleen and the liver was lower than that of PEGylated systems. Our work highlights the importance of generating stable biomolecular coronas in the development of stealth unPEGylated particles, thus providing a connection between the biological behavior of particles in vivo and their synthetic identity

GAS6/TAM signaling pathway controls MICA expression in multiple myeloma cells

NKG2D ligands play a relevant role in Natural Killer (NK) cell -mediated immune surveillance of multiple myeloma (MM). Different levels of regulation control the expression of these molecules at cell surface. A number of oncogenic proteins and miRNAs act as negative regulators of NKG2D ligand transcription and translation, but the molecular mechanisms sustaining their basal expression in MM cells remain poorly understood. Here, we evaluated the role of the growth arrest specific 6 (GAS6)/TAM signaling pathway in the regulation of NKG2D ligand expression and MM recognition by NK cells. Our data showed that GAS6 as well as MERTK and AXL depletion in MM cells results in MICA downregulation and inhibition of NKG2D-mediated NK cell degranulation. Noteworthy, GAS6 derived from bone marrow stromal cells (BMSCs) also increases MICA expression at both protein and mRNA level in human MM cell lines and in primary malignant plasma cells. NF-kB activation is required for these regulatory mechanisms since deletion of a site responsive for this transcription factor compromises the induction of mica promoter by BMSCs. Accordingly, knockdown of GAS6 reduces the capability of BMSCs to activate NF-kB pathway as well as to enhance MICA expression in MM cells. Taken together, these results shed light on molecular mechanism underlying NKG2D ligand regulation and identify GAS6 protein as a novel autocrine and paracrine regulator of basal expression of MICA in human MM cells

SMART REMOTE SENSING THROUGH PASSIVE IMAGING SENSORS: Improvement of Computer Vision Techniques for Real-time Detection, Tracking and Tridimensional Reconstruction.

ENGLISH VERSION Automatic image and video understanding is a pivotal aspect in remote sensing applications involving passive imaging sensors. Among the numerous issues, the detection and tracking of moving objects and the tridimensional reconstruction are of paramount importance in many different fields. Such issues, though widely addressed in the literature, are still lacking of flexible solutions, capable to achieve accuracy and effectiveness while taking into account the aspects of time and costs. This works aims to fill this lack, by proposing efficient real-time solutions that can adapt to different scenarios and that do not require expensive hardware to be performed properly. At first, the detection of challenging moving objects in infrared video sequences acquired by a fixed camera has been tackled. Then, the problem has been extended to the more complex (but also more promising) case of moving camera, focusing on the situation in which it is mounted on an aircraft. Finally, using an airborne camera again, but in the visible domain, the problem of three-dimensionally reconstructing areas and objects of interest from pairs of images has been addressed too. The proposed strategies rely on some typical computer vision techniques, which has been adapted and improved, in order to comply with the above-mentioned desired characteristics. A meticulous evaluation of their performance has been carried out, obtaining very promising results in terms of reliability, accuracy and robustness, as well as in terms of computational time. In the light of this, the proposed solutions are suitable to be applied in a wide variety of different fields, which includes also the most critical ones as security, search and rescue and disaster monitoring. ITALIAN VERSION L'estrazione automatica di informazioni da immagini o video è un aspetto fondamentale nelle applicazioni di telerilevamento da sensori passivi. In particolare, un ruolo di primaria importanza è rivestito dalla rivelazione e dal tracciamento di oggetti in movimento, e dalla ricostruzione tridimensionale. Sebbene tali argomenti siano stati abbondantemente trattati in letteratura, soluzioni accurate e versatili, che puntino al contempo a limitare i tempi e i costi di esecuzione, sono tuttora carenti. Lo scopo di questo lavoro è quello di colmare parzialmente questa mancanza, mediante lo studio e l’implementazione di tecniche efficienti e adattabili a differenti tipi di scenario, che possono essere eseguite in tempo reale e senza bisogno di utilizzare strumentazioni costose. Come prima cosa, è stato affrontato il problema della rivelazione di oggetti in movimento all’interno di sequenze video infrarosse, acquisite da una telecamera ferma. In particolare, sono stati presi in considerazione oggetti che, a causa delle loro caratteristiche, risultano particolarmente difficili da rivelare, come per esempio oggetti molto piccoli, con poco contrasto rispetto allo sfondo, molto veloci o molto lenti. Dopodiché, la trattazione è stata ampliata al caso di telecamera in movimento (più complesso ma anche più interessante in termini di applicabilità), analizzando nello specifico la situazione in cui il dispositivo è trasportato da un aeromobile. Infine, è stato analizzato il problema della ricostruzione tridimensionale realistica di un’area o di un oggetto di interesse a partire da coppie di immagini di essi, sempre utilizzando una telecamera a bordo di un veivolo, ma operante a frequenze visibili. Le strategie proposte si basano su alcune tecniche tipiche della visione artificiale, opportunamente adattate e migliorate per soddisfare le caratteristiche richieste. Dopo essere state implementate, le loro performance sono state valutate approfonditamente dal punto di vista dell’accuratezza, della flessibilità a differenti scenari e del tempo computazionale. I risultati ottenuti si sono rivelati particolarmente promettenti, e hanno indicato come le soluzioni proposte possano essere impiegate in un’ampia gamma di applicazioni in differenti campi, compresi quelli più critici come sicurezza, salvataggio e monitoraggio di disastri naturali e ambientali