Design-centric Method for an Augmented Reality Robotic Surgery

Master'sMASTER OF ENGINEERIN

超音波画像誘導下胎児外科手術のための外部センサを用いない内視鏡三次元画像マッピングシステムの開発

学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 小林 英津子, 東京大学教授 佐久間 一郎, 東京大学教授 大田 順, 東京大学教授 山下 淳, 東京大学教授 中島 義和, 国立成育医療センター副センター長 千葉 敏雄University of Tokyo(東京大学

Semi-FCMNet : semi-supervised learning for forest cover mapping from satellite imagery via ensemble self-training and perturbation

Forest cover mapping is of paramount importance for environmental monitoring, biodiversity assessment, and forest resource management. In the realm of forest cover mapping, significant advancements have been made by leveraging fully supervised semantic segmentation models. However, the process of acquiring a substantial quantity of pixel-level labelled data is prone to time-consuming and labour-intensive procedures. To address this issue, this paper proposes a novel semi-supervised-learning-based semantic segmentation framework that leverages limited labelled and numerous unlabelled data, integrating multi-level perturbations and model ensembles. Our framework incorporates a multi-level perturbation module that integrates input-level, feature-level, and model-level perturbations. This module aids in effectively emphasising salient features from remote sensing (RS) images during different training stages and facilitates the stability of model learning, thereby effectively preventing overfitting. We also propose an ensemble-voting-based label generation strategy that enhances the reliability of model-generated labels, achieving smooth label predictions for challenging boundary regions. Additionally, we designed an adaptive loss function that dynamically adjusts the focus on poorly learned categories and dynamically adapts the attention towards labels generated during both the student and teacher stages. The proposed framework was comprehensively evaluated using two satellite RS datasets, showcasing its competitive performance in semi-supervised forest-cover-mapping scenarios. Notably, the method outperforms the fully supervised approach by 1–3% across diverse partitions, as quantified by metrics including mIoU, accuracy, and mPrecision. Furthermore, it exhibits superiority over other state-of-the-art semi-supervised methods. These results indicate the practical significance of our solution in various domains, including environmental monitoring, forest management, and conservation decision-making processes

Duration biased distribution of clinical and immunological phenotypes in active SLE

IntroductionThis study is aimed to map the clinical and immunological features of active lupus patients with different disease duration.MethodsFor clinical phenotype analysis, we enriched eligible medical records with active SLE (SLEDAI-2k≥8) from the Renji Lupus registry, a single-center database of hospitalized SLE patients with standard care, which covered national-wide patients. Patients with repeated hospitalization records in this enrichment were analyzed longitudinally as validation for the cross-sectional study above.ResultsWe enriched a total of 1313 eligible records on active SLE (SLEDAI-2k≥8) for cross-sectional analysis. Stratified into four groups by a 5-year interval of disease duration, these active SLE patients showed a significantly shifting clinical phenotype along with the duration (ascending nephritis, pulmonary hypertension and descending fever, cutaneous symptoms, arthritis, and neuropsychiatric manifestations), especially in stratifications with disease onset age ≤ 45 years old. A longitudinal analysis of 55 patients with repeated hospitalizations for active lupus showed a similar trend. In the cross-sectional study of 222 records with full information on serology and lymphocyte subsets, peripheral B cell proportion, anti-dsDNA antibody, and serum IgG/IgM negatively correlated with duration, while CD8+ T cell proportion was positively correlated (P values, 0.029-4.8×10-17), which were supported by the sensitivity analysis in patient subgroups according to disease onset age and recent treatment. Multivariate linear regression identified duration as the only significant associator with both B cell and CD8+ T cell proportion (P values, 8.9×10-8 and 7.6×10-5, respectively). These duration biased immune phenotypes were highly consistent with the longitudinal observation in 14 patients with repeated hospitalizations.ConclusionsBoth clinical and immunological features of active SLE are significantly duration biased distributed, which merits further investigations in the evolution of SLE pathogenesis

miR-152 Attenuates the Severity of Lupus Nephritis Through the Downregulation of Macrophage Migration Inhibitory Factor (MIF)-Induced Expression of COL1A1

Background: The role of miR-152 in lupus nephritis has not been elucidated. The aim of this study was to investigate the role of miR-152 in the pathogenesis of lupus nephritis (LN).Methods: miR-152 expression was detected using RT-PCR in LN tissue and normal controls. The miR-152 expression was compared with clinical parameters such as 24 h urine protein excretion level, serum creatinine, and serum complement level and SLEDAI score. The function of miR-152 was examined using human renal proximal tubular epithelial cells (HRPTE). miR-152 mimics and inhibitors were transfected to HRPTEs to ascertain the effects of miR-152.Results: miR-152 expression was downregulated in LN tissue. There was an inverse correlation between miR-152 expression in LN tissue and clinical parameters like 24 h urine protein excretion levels and serum creatinine, but not serum complement levels or SLEDAI. Further analysis showed that macrophage migration inhibitory factor (MIF) was a direct target of miR-152. Downregulation of MIF through complementary binding of miR-152 inhibited the renal expression of COL1A1.Conclusion: miR-152 expression was tapered in LN tissue and miR-152 expression was inversely correlated with chronicity index (CI), serum creatinine and severity of proteinuria. miR-152 may attenuate the severity of LN through the downregulation of MIF-induced expression of COL1A1. These findings suggest that miR-152 may be a potential target for the treatment of LN

A new species of the genus Euxaldar Fennah, 1978 (Hemiptera, Fulgoromorpha, Issidae) from China and revision on the molecular phylogeny of the family

A new species Euxaldar daweishanensis Yang, Chang & Chen, sp. nov. is described and illustrated from southwestern China. The female genitalia of the genus Euxaldar is described and presented for the first time. A checklist and key to the known species of the genus are provided. A revised molecular phylogenetic analysis of the family Issidae based on combined partial sequences of 18S, 28S, COI, and Cytb is provided using both Maximum likelihood and Bayesian inference analyses

Two new species of the tribe Hemisphaeriini (Hemiptera, Fulgoromorpha, Issidae) from southwestern China

Two new species of the tribe Hemisphaeriini: Ceratogergithus brachyspinus Yang & Chen, sp. nov. (Yunnan) and Neohemisphaerius clavatus Yang & Chen, sp. nov. (Guizhou) are described and illustrated. A checklist to Hemisphaeriini genera is provided. The generic characteristics of the genera Ceratogergithus Gnezdilov, 2017 and Neohemisphaerius Chen, Zhang & Chang, 2014 are redefined. Checklists and keys to the species of each genus are given

Design and Development of an Augmented Reality Robotic System for Large Tumor Ablation

International audienceAn augmented reality based robotic system isproposed for treatment of large liver tumor using multipleoverlapping ablations technique. Radiofrequency ablation is anon-resection interventional procedure that minimizesinvasiveness and reduces trauma. A single ablation is howeverlimited by the ablation volume coverage. In treatment of tumorwith diameter that could be 150mm or more, a single needleinsertion will not create sufficient ablation coverage to destroy theentire tumor. As such, multiple insertions are required. Theprecision and consistency associated with robot assisted surgerycoupled with direct augmented reality projection system canbetter facilitate such treatment. The projection system is equippedwith manipulator mechanism and robotic needle insertion arm formultiple insertions and needle deployment. The prototypeaugmented reality surgical system was evaluated on its abilities inablating large tumor. Virtual models of the rectangular robot forprojector manipulation and robotic needle insertion device werealso used to assess the effectiveness of the proposed AR design

Detect-Focus-Track-Servo (DFTS): A vision-based workflow algorithm for robotic image-guided micromanipulation

Robotic image-guided micromanipulation contributes towards the ease of operation, speed, accuracy, and repeatability in cell manipulation. However, such technology is not fully exploited because of the challenges in the integration of robotic modules with existing microscope systems, and the difficulty in incorporating robot assistance seamlessly into the workflow. In this paper, we propose a vision-based workflow algorithm termed Detect-Focus-Track-Servo (DFTS). It facilitates easy integration of robotic modules. It also supports user interactions while minimizing the need for manual intervention and disruption to workflow through automatic detection, focusing, tracking and servoing. Experimental results suggest satisfactory detection accuracy of 99.0 % at 70 μm tolerance. The robustness test suggests no difference in the accuracy under blurred and cluttered images. The self-focus algorithm is also demonstrated to bring the tip into focus consistently. The track-servo algorithm achieves low sub-pixel uncertainty. By proposing the DFTS workflow algorithm, we hope that the level of autonomy and ease of deployment in robot and vision modules for micromanipulation can be improved so as to open up new possibilities in the development of robotic image-guided cell manipulation.SUTD-MIT International Design Centre (IDC