Intraoperative identification of underlying major venous and arterial vessels using freehand diffuse optical spectroscopy imaging (freeDOSi) for guiding minimally invasive surgery: an in vivo demonstration in a pig model (Conference Presentation)

2018 ◽  
Author(s):  
Daqing Piao ◽  
Mohammad Ramadan ◽  
Aaron Park ◽  
Kenneth E. Bartels ◽  
Sanjay Patel
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Optical Spectroscopy ◽  
Invasive Surgery ◽  
Pig Model ◽  
Diffuse Optical Spectroscopy

scholarly journals Real-Time Expanded Field-of-View for Minimally Invasive Surgery Using Multi-Camera Visual Simultaneous Localization and Mapping

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2106
Author(s):  
Ahmed Afifi ◽  
Chisato Takada ◽  
Yuichiro Yoshimura ◽  
Toshiya Nakaguchi
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Real Time ◽  
Invasive Surgery ◽  
Simultaneous Localization And Mapping ◽  
Field Of View ◽  
Time Dynamic ◽  
Matrix Estimation ◽  
Localization And Mapping

Minimally invasive surgery is widely used because of its tremendous benefits to the patient. However, there are some challenges that surgeons face in this type of surgery, the most important of which is the narrow field of view. Therefore, we propose an approach to expand the field of view for minimally invasive surgery to enhance surgeons’ experience. It combines multiple views in real-time to produce a dynamic expanded view. The proposed approach extends the monocular Oriented features from an accelerated segment test and Rotated Binary robust independent elementary features—Simultaneous Localization And Mapping (ORB-SLAM) to work with a multi-camera setup. The ORB-SLAM’s three parallel threads, namely tracking, mapping and loop closing, are performed for each camera and new threads are added to calculate the relative cameras’ pose and to construct the expanded view. A new algorithm for estimating the optimal inter-camera correspondence matrix from a set of corresponding 3D map points is presented. This optimal transformation is then used to produce the final view. The proposed approach was evaluated using both human models and in vivo data. The evaluation results of the proposed correspondence matrix estimation algorithm prove its ability to reduce the error and to produce an accurate transformation. The results also show that when other approaches fail, the proposed approach can produce an expanded view. In this work, a real-time dynamic field-of-view expansion approach that can work in all situations regardless of images’ overlap is proposed. It outperforms the previous approaches and can also work at 21 fps.

Design and preliminary in vivo validation of a robotic laparoscope holder for minimally invasive surgery

2009 ◽  
Vol 5 (3) ◽  
pp. 319-326 ◽  
Author(s):  
Benoît Herman ◽  
Bruno Dehez ◽  
Khanh Tran Duy ◽  
Benoît Raucent ◽  
Etienne Dombre ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
In Vivo Validation

Recent advances in the CoBRASurge robotic manipulator and dexterous miniature in vivo robotics for minimally invasive surgery

2010 ◽  
Vol 224 (7) ◽  
pp. 1487-1494 ◽  
Author(s):  
A C Lehman ◽  
M M Tiwari ◽  
B C Shah ◽  
S M Farritor ◽  
C A Nelson ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Peritoneal Cavity ◽  
Invasive Surgery ◽  
Da Vinci ◽  
Miniature Robots ◽  
Tissue Manipulation ◽  
External Incisions ◽  
Single Insertion

Minimally invasive surgery (MIS) reduces trauma and improves patient recovery. Traditional laparoscopic procedures are performed using multiple long, thin tools that are inserted through small incisions in the abdominal wall. The advantages of these procedures are often restricted to less complicated procedures owing to imaging and tissue manipulation limitations. These limitations can be overcome using advanced surgical systems, such as da Vinci®, that provide the surgeon with enhanced visualization and improved tool dexterity. However, the da Vinci system is expensive and occupies significant space in the operating room. The compact bevel-geared robot for advanced surgery, CoBRASurge, is a compact robotic system that addresses the space and expense limitations of large external robotic systems. This system provides a stable platform for laparoscopic tool manoeuvring, while also allowing the surgical team improved access to the patient. New methods for performing MIS, including single incision and natural orifice access, are also being developed to further minimize invasiveness through reducing or eliminating external incisions. However, the instruments for these procedures are further limited by accessing the peritoneal cavity through a single insertion point. Dexterous miniature robots that are completely inserted into the peritoneal cavity are being developed that mitigate these limitations to provide improved triangulation.

scholarly journals Analyzing Liver Surface Indentation for In Vivo Refinement of Tumor Location in Minimally Invasive Surgery

2020 ◽  
Author(s):  
Yingqiao Yang ◽  
Kai-Leung Yung ◽  
Tin Wai Robert Hung ◽  
Kai-Ming Yu
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Invasive Surgery ◽  
Surface Deformation ◽  
Angular Position ◽  
Radial Distance ◽  
Tumor Location ◽  
Porcine Liver ◽  
Optimal Material

AbstractManual palpation to update the position of subsurface tumor(s) is a normal practice in open surgery, but is not possible through the small incisions of minimally invasive surgery (MIS). This paper proposes a method that has the potential to use a simple constant-force indenter and the existing laparoscopic camera for tumor location refinement in MIS. The indenter floats with organ movement to generate a static surface deformation on the soft tissue, resolving problems of previous studies that require complicated measurement of force and displacement during indentation. By analyzing the deformation profile, we can intraoperatively update the tumor’s location in real-time. Indentation experiments were conducted on healthy and “diseased” porcine liver specimens to obtain the deformation surrounding the indenter site. An inverse finite element (FE) algorithm was developed to determine the optimal material parameters of the healthy liver tissue. With these parameters, a computational model of tumorous tissue was constructed to quantitatively evaluate the effects of the tumor location on the induced deformation. By relating the experimental data from the “diseased” liver specimen to the computational results, we estimated the radial distance between the tumor and the indenter, as well as the angular position of the tumor relative to the indenter.

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