A5075586895- 3D Surveying and Cultural Heritage
- Surgical Simulation and Training
- Advanced Vision and Imaging
- Machine Learning in Healthcare
- Currency Recognition and Detection
- Machine Fault Diagnosis Techniques
- Electronic Health Records Systems
- Artificial Intelligence in Healthcare and Education
- Robotics and Sensor-Based Localization
- Hydraulic and Pneumatic Systems
- Sepsis Diagnosis and Treatment
- Advanced Neural Network Applications
- Anatomy and Medical Technology
The stereo correspondence and reconstruction of endoscopic data sub-challenge was organized during the Endovis challenge at MICCAI 2019 in Shenzhen, China. task to perform dense depth estimation using 7 training datasets 2 test sets structured light captured porcine cadavers. These were provided by a team Intuitive Surgical. 10 teams participated day. This paper contains 3 additional methods which submitted after finished as well supplemental section from these on issues they found with dataset.
Intensive care clinicians need reliable clinical practice tools to preempt unexpected critical events that might harm their patients in intensive units (ICU), pre-plan timely interventions, and keep the patient's family well informed. The conventional statistical models are built by curating only a limited number of key variables, which means vast unknown amount potentially precious data remains unused. Deep learning (DLMs) can be leveraged learn from large complex datasets construct...
You have accessJournal of UrologySurgical Technology & Simulation: Instrumentation I (MP10)1 Sep 2021MP10-10 COMPLEXITIES IN ANNOTATING SURGICAL VIDEOS TO BUILD SUPERVISED DEEP LEARNING MODELS FOR LAPAROSCOPIC LIVE DONOR NEPHRECTOMY Mahendra Bhandari, Hamid Ali, Mahesh Desai, C. Mallikarjuna, Aneesh Srivastava, Deepak Dubey, Vipin Tyagi, Rajesh Ahlawat, Carolyn Pratt, Gautum Ram Chaudhary, Trevor Zeffiro, and Madhu Reddiboina BhandariMahendra Bhandari More articles by this author , AliHamid...