Application of Image and Video Analysis in Robotics Technology for Minimally Invasive Surgery
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Biomedical Engineering".
Deadline for manuscript submissions: closed (20 August 2023) | Viewed by 659
Special Issue Editors
Interests: image-guided video assisted thoracoscopic surgery; robot-assisted minimally invasive esophagectomy; robotic sympathetic nerve reconstruction; robot-assisted minimally invasive surgery
2. Chang Gung Memorial Hospital, Taoyuan, Taiwan
3. Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan, Taiwan
Interests: deep learning; metaverse; web 3.0; computer vision; radiology; radiation oncology; surgical oncology; POCUS
Special Issue Information
Dear Colleagues,
We are pleased to invite submissions to a new Special Issue titled “Application of Image and Video Analysis in Robotics Technology for Minimally Invasive Surgery”. The diffusion of minimally invasive surgery and robotic assistance has thrived in recent years. However, there are some issues that limit its widespread adoption, including its limited field of view, lack of haptic feedback, loss of depth perception, extended learning curve, prolonged operative times, and higher financial costs.
To overcome these issues, digital technologies such as artificial intelligence and the metaverse are constantly being developed to revolutionize operating rooms according to Moore's Law of computation. With current surgical platforms, multiple sensor arrays, such as immunofluorescence, infrared radiation, nerve stimulators, and classic imaging with ultrasound/CT/MRI, are deployed to augment surgical procedures. Analyzing the signals and videos generated from these instruments has enormous potential to improve surgical skills and prognoses. For example, real-time tissue tracking on the screen may designate some areas as “no-fly zones,” and the control mechanisms of the robotic platform may block the robot from those zones, thereby producing a safe work environment for both surgical teams and patients.
From this arises the necessity for high-quality common datasets that allow the scientific community to perform comparative benchmarking and the validation of digital technologies. A high-profile international challenge, EndoVis, has been organized at MICCAI each year and contains a large collection of publicly accessible datasets comprising various computer vision tasks (classification, detection, segmentation, etc.) and subdisciplines ranging from laparoscopy to coloscopy and surgical training. Those who have participated in challenges such as EndoVis are highly encouraged to share their achievements and experiences in this Special Issue.
Together, we can learn from robots, just as how they are learning from us.
Dr. Yin-Kai Chao
Dr. Shih-Chun Cheng
Guest Editors
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Keywords
- tissue tracking
- surgical tool evaluation
- surgical action recognition
- three-dimensional scene reconstruction
- preoperative to intraoperative registration
- surgical workflow analysis
- surgical skill assessment
- computer vision and artificial intelligence
- metaverse
- minimally invasive surgery and robotic assistance
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