Assessment of valve regurgitation severity via contrastive learning and multi-view video integration.

Objective. This paper presents a novel approach for addressing the intricate task of diagnosing aortic valve regurgitation (AR), a valvular disease characterized by blood leakage due to incompetence of the valve closure. Conventional diagnostic techniques require detailed evaluations of multi-modal clinical data, frequently resulting in labor-intensive and time-consuming procedures that are vulnerable to varying subjective assessment of regurgitation severity.Approach. In our research, we introduce the multi-view video contrastive network, designed to leverage multiple color Doppler imaging inputs for multi-view video processing. We leverage supervised contrastive learning as a strategic approach to tackle class imbalance and enhance the effectiveness of our feature representation learning. Specifically, we introduce a contrastive learning framework to enhance representation learning within the embedding space through inter-patient and intra-patient contrastive loss terms.Main results. We conducted extensive experiments using an in-house dataset comprising 250 echocardiography video series. Our results exhibit a substantial improvement in diagnostic accuracy for AR compared to state-of-the-art methods in terms of accuracy by 9.60%, precision by 8.67%, recall by 9.01%, andF1-score by 8.92%. These results emphasize the capacity of our approach to provide a more precise and efficient method for evaluating the severity of AR.Significance. The proposed model could quickly and accurately make decisions about the severity of AR, potentially serving as a useful prescreening tool.

3D Boolean operations in virtual surgical planning.

PURPOSE: Boolean operations in computer-aided design or computer graphics are a set of operations (e.g. intersection, union, subtraction) between two objects (e.g. a patient model and an implant model) that are important in performing accurate and reproducible virtual surgical planning. This requires accurate and robust techniques that can handle various types of data, such as a surface extracted from volumetric data, synthetic models, and 3D scan data. METHODS: This article compares the performance of the proposed method (Boolean operations by a robust, exact, and simple method between two colliding shells (BORES)) and an existing method based on the Visualization Toolkit (VTK). RESULTS: In all tests presented in this article, BORES could handle complex configurations as well as report impossible configurations of the input. In contrast, the VTK implementations were unstable, do not deal with singular edges and coplanar collisions, and have created several defects. CONCLUSIONS: The proposed method of Boolean operations, BORES, is efficient and appropriate for virtual surgical planning. Moreover, it is simple and easy to implement. In future work, we will extend the proposed method to handle non-colliding components.

[Orthognathic mandibular osteotomy and condyle positioning: update and innovation]. / Ostéotomie mandibulaire orthognathique et positionnement condylien : point et innovation.

The temporomandibular joints function in synergy with the dental occlusion within the manducatory system. Orthodontists and surgeons must take into account the condylar position since any problem related to positioning of the condyle could result in occlusal disorders including relapse and the risk of occurrence, decompensation or worsening of temporomandibular dysfunction. We wanted to answer three questions: What is the position of the condyle following orthognathic surgery? What benefit is there in repositioning the condyle? What means are available to check condylar position? Finally, in the light of the answers, we describe an innovative occlusal and condylar positioning device for mandibular osteotomies based on computer-assisted surgical planning techniques. It consists of a three-dimensional, printed guide enabling surgeons to position the condyles as desired. It is accurate, simple, reproducible, independent of operator experience as well as rapid and economical.

Anthropological facial approximation in three dimensions (AFA3D): computer-assisted estimation of the facial morphology using geometric morphometrics.

This study presents Anthropological Facial Approximation in Three Dimensions (AFA3D), a new computerized method for estimating face shape based on computed tomography (CT) scans of 500 French individuals. Facial soft tissue depths are estimated based on age, sex, corpulence, and craniometrics, and projected using reference planes to obtain the global facial appearance. Position and shape of the eyes, nose, mouth, and ears are inferred from cranial landmarks through geometric morphometrics. The 100 estimated cutaneous landmarks are then used to warp a generic face to the target facial approximation. A validation by re-sampling on a subsample demonstrated an average accuracy of c. 4 mm for the overall face. The resulting approximation is an objective probable facial shape, but is also synthetic (i.e., without texture), and therefore needs to be enhanced artistically prior to its use in forensic cases. AFA3D, integrated in the TIVMI software, is available freely for further testing.