Artificial Intelligence Technologies in the Microsurgical Operating Room (Review)
暂无分享,去创建一个
A. Bykanov | D. Pitskhelauri | G. Danilov | V.V. Kostumov | O.G. Pilipenko | B.M. Nutfullin | O.A. Rastvorova
[1] A. Cohen-Gadol,et al. Image Segmentation of Operative Neuroanatomy Into Tissue Categories Using a Machine Learning Construct and Its Role in Neurosurgical Training , 2022, Operative neurosurgery.
[2] Anima Anandkumar,et al. Validation of Machine Learning–Based Automated Surgical Instrument Annotation Using Publicly Available Intraoperative Video , 2022, Operative neurosurgery.
[3] R. Liao,et al. Differentiating solitary brain metastases from glioblastoma by radiomics features derived from MRI and 18F-FDG-PET and the combined application of multiple models , 2022, Scientific Reports.
[4] Zijian Zhao,et al. Towards Surgical Tools Detection and Operative Skill Assessment Based on Deep Learning , 2022, IEEE Transactions on Medical Robotics and Bionics.
[5] Anima Anandkumar,et al. Expert Surgeons and Deep Learning Models Can Predict the Outcome of Surgical Hemorrhage from One Minute of Video , 2022, medRxiv.
[6] Fernando Pérez-Escamirosa,et al. Development of a 3D Motion Tracking System for the Analysis of Skills in Microsurgery , 2021, Journal of Medical Systems.
[7] O. Commowick,et al. Multiple sclerosis lesions segmentation from multiple experts: The MICCAI 2016 challenge dataset , 2021, NeuroImage.
[8] Marcelo Magaldi Oliveira,et al. Computer vision coaching microsurgical laboratory training: PRIME (Proficiency Index in Microsurgical Education) proof of concept , 2021, Neurosurgical Review.
[9] Sidong Liu,et al. Machine Learning for the Prediction of Molecular Markers in Glioma on Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis , 2021, Neurosurgery.
[10] A. Bykanov,et al. Effect of Energy Drinks on Microsurgical Hand Tremor , 2021, Plastic and Reconstructive Surgery, Global Open.
[11] P. Zinn,et al. MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift , 2021, Journal of clinical medicine.
[12] Yu Zhang,et al. Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features , 2021, Annals of translational medicine.
[13] A.A. Litvin,et al. Radiomics and Digital Image Texture Analysis in Oncology (Review) , 2021, Sovremennye tekhnologii v meditsine.
[14] Thomas M. Ward,et al. Computer vision in surgery. , 2020, Surgery.
[15] Yudong Zhang,et al. A Review of Deep Learning on Medical Image Analysis , 2020, Mobile Networks and Applications.
[16] Thomas S. Lendvay,et al. Bidirectional long short-term memory for surgical skill classification of temporally segmented tasks , 2020, International Journal of Computer Assisted Radiology and Surgery.
[17] L. Likhterman. Healing: standards and art , 2020, Russian journal of neurosurgery.
[18] V. Lowe,et al. Prediction of MGMT Status for Glioblastoma Patients Using Radiomics Feature Extraction from 18F-DOPA-PET Imaging. , 2020, International journal of radiation oncology, biology, physics.
[19] Ryan L. Steinberg,et al. MP34-06 MACHINE LEARNING USING A MULTI-TASK CONVOLUTIONAL NEURAL NETWORKS CAN ACCURATELY ASSESS ROBOTIC SKILLS , 2020 .
[20] R. Del Maestro,et al. Artificial Intelligence Distinguishes Surgical Training Levels in a Virtual Reality Spinal Task , 2019, The Journal of bone and joint surgery. American volume.
[21] Nykan Mirchi,et al. Machine Learning Identification of Surgical and Operative Factors Associated With Surgical Expertise in Virtual Reality Simulation. , 2019, JAMA network open.
[22] Ehsan T. Esfahani,et al. Surgical Skill Assessment using Motor Control Features and Hidden Markov Model , 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[23] Didier Mutter,et al. Learning from a tiny dataset of manual annotations: a teacher/student approach for surgical phase recognition , 2018, ArXiv.
[24] Hyunjin Park,et al. Classification of the glioma grading using radiomics analysis , 2018, PeerJ.
[25] Youssef Ahmed,et al. A computer vision technique for automated assessment of surgical performance using surgeons’ console-feed videos , 2018, International Journal of Computer Assisted Radiology and Surgery.
[26] Yuan Xing,et al. An automatic skill evaluation framework for robotic surgery training , 2018, The international journal of medical robotics + computer assisted surgery : MRCAS.
[27] Wenzhen Zhu,et al. Radiomics based on multicontrast MRI can precisely differentiate among glioma subtypes and predict tumour-proliferative behaviour , 2018, European Radiology.
[28] A. Ghanem,et al. Microsurgery Competency During Plastic Surgery Residency: An Objective Skills Assessment of an Integrated Residency Training Program , 2018, Eplasty.
[29] Anthony Jarc,et al. Utilizing Machine Learning and Automated Performance Metrics to Evaluate Robot-Assisted Radical Prostatectomy Performance and Predict Outcomes. , 2018, Journal of endourology.
[30] Jonathan Krause,et al. Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks , 2018, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[31] Yuan Xing,et al. Evaluation of robotic surgery skills using dynamic time warping , 2017, Comput. Methods Programs Biomed..
[32] Rajnikant V. Patel,et al. Energy-Based Metrics for Arthroscopic Skills Assessment , 2017, Sensors.
[33] Jason J. Corso,et al. Detection and Localization of Robotic Tools in Robot-Assisted Surgery Videos Using Deep Neural Networks for Region Proposal and Detection , 2017, IEEE Transactions on Medical Imaging.
[34] Tobias Schuldt,et al. Positioning Accuracy in Otosurgery Measured with Optical Tracking , 2016, PloS one.
[35] Andru Putra Twinanda,et al. EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos , 2016, IEEE Transactions on Medical Imaging.
[36] Akio Morita,et al. Assessing Microneurosurgical Skill with Medico-Engineering Technology. , 2015, World neurosurgery.
[37] Gordon K. Lee,et al. Motion Analysis for Microsurgical Training: Objective Measures of Dexterity, Economy of Movement, and Ability , 2015, Plastic and reconstructive surgery.
[38] Masaru Ishii,et al. Automated objective surgical skill assessment in the operating room from unstructured tool motion in septoplasty , 2015, International Journal of Computer Assisted Radiology and Surgery.
[39] O. Weede,et al. Movement Analysis for Surgical Skill Assessment and Measurement of Ergonomic Conditions , 2014, 2014 2nd International Conference on Artificial Intelligence, Modelling and Simulation.
[40] Gordon K. Lee,et al. The Stanford Microsurgery and Resident Training (SMaRT) Scale: Validation of an On-Line Global Rating Scale for Technical Assessment , 2013, Annals of plastic surgery.
[41] Patrick Granton,et al. Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.
[42] Xianghong Ma,et al. The effect of supporting a surgeon's wrist on their hand tremor , 2010, Microsurgery.
[43] Blake Hannaford,et al. Markov modeling of minimally invasive surgery based on tool/tissue interaction and force/torque signatures for evaluating surgical skills , 2001, IEEE Transactions on Biomedical Engineering.
[44] V. Krylov,et al. [Neurosurgery in Russian Federation]. , 2017, Voprosy neirokhirurgii imeni N N Burdenko.
[45] Henry C. Lin,et al. JHU-ISI Gesture and Skill Assessment Working Set ( JIGSAWS ) : A Surgical Activity Dataset for Human Motion Modeling , 2014 .