The international journal of medical robotics + computer assisted surgery : MRCAS最新文献_第3页

Multidimensional Sensory Attention Enhancement Method for Lower Limb Rehabilitation Training. 下肢康复训练的多维感觉注意增强方法。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2026-04-01 DOI: 10.1002/rcs.70168

Yi Yang, Ling He, Donghua Zheng, Difu Wang, Yinhong An, Zhijun Yue

{"title":"Multidimensional Sensory Attention Enhancement Method for Lower Limb Rehabilitation Training.","authors":"Yi Yang, Ling He, Donghua Zheng, Difu Wang, Yinhong An, Zhijun Yue","doi":"10.1002/rcs.70168","DOIUrl":"10.1002/rcs.70168","url":null,"abstract":"Background: Maintaining attention is essential for effective lower limb rehabilitation, yet repetitive exercises often cause focus loss. Existing methods lack real-time quantitative assessment, limiting adaptive training adjustments.Methods: This study developed an electroencephalogram (EEG)-based attention model integrating auditory, visual, and tactile stimuli. Event-related desynchronisation (ERD) and movement-related cortical potentials (MRCP) were extracted and fused using principal component analysis (PCA) to quantify attention on a 0-5 scale. EEG preprocessing included spatial correction, artefact removal, and band optimisation.Results: The proposed model effectively quantified attention states and identified optimal sensory combinations. Multisensory stimulation, especially red light with 60 dB sound and external force, significantly enhanced cortical engagement. The system achieved 91.7% sensitivity in detecting attention decline under interference conditions.Conclusions: The multidimensional sensory attention enhancement method enables dynamic attention monitoring and adaptive feedback in rehabilitation training, supporting future clinical applications and large-scale validation.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70168"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147719133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Does Robotic Adrenalectomy Outperform Laparoscopic Approaches in Obese Patients? A Systematic Review and Subgroup Meta-Analysis of 1,107 Patients. 机器人肾上腺切除术在肥胖患者中优于腹腔镜手术吗？1107例患者的系统评价和亚组荟萃分析。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2026-04-01 DOI: 10.1002/rcs.70169

Ahmed Abdelsamad, Youssef Badie, Mohamed Elfakharany, Mohamed Elatrosh, Mohamed Elgohary, Eslam Elmaghraby, Florian Gebauer, Ralf Mike Langenbach, Khaled Mohamed

{"title":"Does Robotic Adrenalectomy Outperform Laparoscopic Approaches in Obese Patients? A Systematic Review and Subgroup Meta-Analysis of 1,107 Patients.","authors":"Ahmed Abdelsamad, Youssef Badie, Mohamed Elfakharany, Mohamed Elatrosh, Mohamed Elgohary, Eslam Elmaghraby, Florian Gebauer, Ralf Mike Langenbach, Khaled Mohamed","doi":"10.1002/rcs.70169","DOIUrl":"10.1002/rcs.70169","url":null,"abstract":"Background: Obesity poses technical challenges in adrenalectomy. Robotic adrenalectomy (RA) offers advantages over laparoscopic adrenalectomy (LA), but evidence in obese patients remains limited.Methods: A meta-analysis of comparative studies through 2025 assessed perioperative outcomes of RA versus LA, with subgroup analyses by body habitus (obese vs. non-obese) and surgical approach (lateral transabdominal [LT] vs. posterior retroperitoneal [PR]). Primary outcomes included operative time (OT), blood loss (EBL), hospital stay (LOHS), complications, conversion, and mortality. Study quality was evaluated using the Newcastle-Ottawa Scale, and certainty was assessed using the GRADE approach.Results: Eight studies (1107 patients) were included. RA was associated with reduced EBL (p < 0.001) and shorter LOHS (p < 0.001), with no other significant differences. Subgroup analysis showed shorter LOHS in non-obese LA patients (p = 0.03). PR showed a shorter LOHS (p = 0.001) compared with LT.Conclusions: RA provides perioperative benefits, particularly reduced blood loss and shorter hospital stay, without compromising safety.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70169"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13094886/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147730942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

EA-Net: Edge Attention Network for Brain Tumour Segmentation in MRI. EA-Net: MRI中脑肿瘤分割的边缘注意网络。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2026-04-01 DOI: 10.1002/rcs.70163

Meng Fansheng, Duan Xingguang, Song Xinya, Fang Fengxinyun, Tian Jiexi, Wang Xujia, Chen Yu, Zhao Yuanli, Li Changsheng

{"title":"EA-Net: Edge Attention Network for Brain Tumour Segmentation in MRI.","authors":"Meng Fansheng, Duan Xingguang, Song Xinya, Fang Fengxinyun, Tian Jiexi, Wang Xujia, Chen Yu, Zhao Yuanli, Li Changsheng","doi":"10.1002/rcs.70163","DOIUrl":"10.1002/rcs.70163","url":null,"abstract":"Background: Accurate brain tumour segmentation is crucial for clinical diagnosis and treatment planning, yet remains challenging due to the scale diversity of tumour regions, ambiguous boundary structures, and highly irregular shapes.Methods: We propose a novel Edge Attention Network that integrates two key components: a Multi-Scale Context Fusion Module to dynamically adjust receptive fields and capture multi-scale contextual information, and an Edge Segmentation Module that explicitly extracts tumour boundaries and injects them into the backbone as spatial attention to refine segmentation details, particularly at edges.Results: Experiments show that our model achieves Dice coefficients of 90.37% for Tumour Core (TC) and 88.91% for Whole Tumour (WT) on the BraTS2021 dataset. In cross-dataset generalisation tests on BTM-PVS, it maintains strong performance with 75.20% TC and 74.20% WT.Conclusions: The proposed method demonstrates superior segmentation accuracy and robust generalisation capability, highlighting its clinical potential and offering new insights for medical image segmentation.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70163"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147663422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Explainable Lightweight Model Using Low-Rank and Convolutional Block Attention for Pancreatic Cancer Diagnosis. 使用低秩和卷积块注意的可解释轻量级模型用于胰腺癌诊断。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2026-04-01 DOI: 10.1002/rcs.70164

Vishesh Tanwar, Bhisham Sharma, Dhirendra Prasad Yadav, Panos Liatsis

{"title":"Explainable Lightweight Model Using Low-Rank and Convolutional Block Attention for Pancreatic Cancer Diagnosis.","authors":"Vishesh Tanwar, Bhisham Sharma, Dhirendra Prasad Yadav, Panos Liatsis","doi":"10.1002/rcs.70164","DOIUrl":"10.1002/rcs.70164","url":null,"abstract":"Background: Early and accurate pancreatic cancer (PC) detection remains a major clinical challenge.Methods: We introduce a novel hybrid deep learning framework for automated classification of CT images, which requires fewer computational resources while achieving high diagnostic performance. We integrated a lightweight MobileNetV3Small backbone with a convolutional block attention module and Low-rank Attention with Shared Efficient Representations (LASER) to enhance feature representation. Feature maps are projected via a 1 × 1 convolution into token sequences and processed through a transformer encoder to capture long-range dependencies. A parallel global average pooling extracts aggregated features, fused using a cross-type interaction (CTI) module.Results: The model was evaluated on 18,942 CT images and achieved 99.34% accuracy, AUC-ROC of 0.9996, Cohen's Kappa of 0.9897, and MCC of 0.9859, outperforming ResNet50, EfficientNetB0, and ViT variants with only 1.26 million parameters.Conclusions: Explainability analyses using Grad-CAM, Grad-CAM++, and attention visualisation suggest that the model focuses on clinically relevant regions.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"22 2","pages":"e70164"},"PeriodicalIF":0.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13091572/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147719164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Modelling of the Surgery Arm in Sina_flex Robotic Telesurgery System. Sinaflex机器人远程手术系统手术臂的动力学建模。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2025-08-01 DOI: 10.1002/rcs.70093

Ramazan Rajabi, Mehrnaz Aghanouri, Hamid Moradi, Alireza Mirbagheri

{"title":"Dynamic Modelling of the Surgery Arm in Sinaflex Robotic Telesurgery System.","authors":"Ramazan Rajabi, Mehrnaz Aghanouri, Hamid Moradi, Alireza Mirbagheri","doi":"10.1002/rcs.70093","DOIUrl":"https://doi.org/10.1002/rcs.70093","url":null,"abstract":"Background: The use of robotic telesurgery has increased because of its high accuracy, fewer complications, and remote-control capability. To improve the accuracy of robotic arms in these systems, it is essential to have a precise dynamic model.Methods: In this study, we focus on the Sinaflex robotic telesurgery system and develop a dynamic model for a novel slave robot. Our approach involves deriving and linearising dynamic equations, defining optimal excitation trajectories, and estimating dynamic parameters using least square optimisation. To investigate the parameters' identification accuracy, the joint torques predicted by the model were compared with those actually obtained from the experiments.Results: The results reveal that the method accurately predicts joint torques with the root mean square ( RMS) ranging from 0.58 to 1.48 Nm.Conclusions: Using the proposed method in this paper for identifying the robot dynamic parameters leads to more accurate results for robots with complex mechanisms.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":"21 4","pages":"e70093"},"PeriodicalIF":0.0,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144801190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparison of robotic and open central pancreatectomy. 机器人与开放式中央胰切除术的比较。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2023-06-08 DOI: 10.14701/ahbps.2023s1.bp-pp-4-7

Man-Ling Wang, Bor-Shiuan Shyr, Shih-Chin Chen, Shin-E Wang, Y. Shyr, B. Shyr

引用次数: 0

Full coverage path planning algorithm for MRgFUS therapy MRgFUS治疗全覆盖路径规划算法

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2022-03-07 DOI: 10.1002/rcs.2389

A. Antoniou, A. Georgiou, N. Evripidou, C. Damianou

引用次数: 3

A deep learning framework for real‐time 3D model registration in robot‐assisted laparoscopic surgery 机器人辅助腹腔镜手术中实时3D模型注册的深度学习框架

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2022-03-04 DOI: 10.1002/rcs.2387

Erica Padovan, Giorgia Marullo, L. Tanzi, P. Piazzolla, Sandro Moos, F. Porpiglia, E. Vezzetti

引用次数: 9

A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm. 在肠道和口腔颌面外科远程呈现中使用混合现实技术的新方案：三维平均值克隆算法。

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2020-09-04 DOI: 10.1002/rcs.2161

Arjina Maharjan, Abeer Alsadoon, P W C Prasad, Nada AlSallami, Tarik A Rashid, Ahmad Alrubaie, Sami Haddad

{"title":"A Novel Solution of Using Mixed Reality in Bowel and Oral and Maxillofacial Surgical Telepresence: 3D Mean Value Cloning algorithm.","authors":"Arjina Maharjan, Abeer Alsadoon, P W C Prasad, Nada AlSallami, Tarik A Rashid, Ahmad Alrubaie, Sami Haddad","doi":"10.1002/rcs.2161","DOIUrl":"10.1002/rcs.2161","url":null,"abstract":"Background and aim: Most of the Mixed Reality models used in the surgical telepresence are suffering from the discrepancies in the boundary area and spatial-temporal inconsistency due to the illumination variation in the video frames. The aim behind this work is to propose a new solution that helps produce the composite video by merging the augmented video of the surgery site and virtual hand of the remote expertise surgeon. The purpose of the proposed solution is to decrease the processing time and enhance the accuracy of merged video by decreasing the overlay and visualization error and removing occlusion and artefacts.Methodology: The proposed system enhanced the mean value cloning algorithm that helps to maintain the spatial-temporal consistency of the final composite video. The enhanced algorithm includes the 3D mean value coordinates and improvised mean value interpolant in the image cloning process, which helps to reduce the sawtooth, smudging and discoloration artefacts around the blending region RESULTS: As compared to the state of art solution, the accuracy in terms of overlay error of the proposed solution is improved from 1.01mm to 0.80mm whereas the accuracy in terms of visualization error is improved from 98.8% to 99.4%. The processing time is reduced to 0.173 seconds from 0.211 seconds CONCLUSION: Our solution helps make the object of interest consistent with the light intensity of the target image by adding the space distance that helps maintain the spatial consistency in the final merged video. This article is protected by copyright. All rights reserved.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":" ","pages":"e2161"},"PeriodicalIF":0.0,"publicationDate":"2020-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38440926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Novel Visualization System of Using Augmented Reality in Knee Replacement Surgery: Enhanced Bidirectional Maximum CorrentropyAlgorithm. 在膝关节置换手术中使用增强现实技术的新型可视化系统：增强型双向最大熵算法

The international journal of medical robotics + computer assisted surgery : MRCAS Pub Date : 2020-09-01 DOI: 10.1002/rcs.2154

Nitish Maharjan, Abeer Alsadoon, P W C Prasad, Salma Abdullah, Tarik A Rashid

{"title":"A Novel Visualization System of Using Augmented Reality in Knee Replacement Surgery: Enhanced Bidirectional Maximum CorrentropyAlgorithm.","authors":"Nitish Maharjan, Abeer Alsadoon, P W C Prasad, Salma Abdullah, Tarik A Rashid","doi":"10.1002/rcs.2154","DOIUrl":"10.1002/rcs.2154","url":null,"abstract":"Background and aim: Image registration and alignment are the main limitations of augmented reality-based knee replacement surgery. This research aims to decrease the registration error, eliminate outcomes that are trapped in local minima to improve the alignment problems, handle the occlusion and maximize the overlapping parts.Methodology: markerless image registration method was used for Augmented reality-based knee replacement surgery to guide and visualize the surgical operation. While weight least square algorithm was used to enhance stereo camera-based tracking by filling border occlusion in right to left direction and non-border occlusion from left to right direction.Results: This study has improved video precision to 0.57 mm ∼ 0.61 mm alignment error. Furthermore, with the use of bidirectional points, i.e. Forwards and backwards directional cloud point, the iteration on image registration was decreased. This has led to improved the processing time as well. The processing time of video frames was improved to 7.4 ∼11.74 fps.Conclusions: It seems clear that this proposed system has focused on overcoming the misalignment difficulty caused by movement of patient and enhancing the AR visualization during knee replacement surgery. The proposed system was reliable and favourable which helps in eliminating alignment error by ascertaining the optimal rigid transformation between two cloud points and removing the outliers and non-Gaussian noise. The proposed augmented reality system helps in accurate visualization and navigation of anatomy of knee such as femur, tibia, cartilage, blood vessels, etc. This article is protected by copyright. All rights reserved.","PeriodicalId":75029,"journal":{"name":"The international journal of medical robotics + computer assisted surgery : MRCAS","volume":" ","pages":"e2154"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38335714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0