Hand-held robotic device for laparoscopic surgery and training

Author(s):  
Ricardo Pereira ◽  
Antonio H.J. Moreira ◽  
Mariana Leite ◽  
Pedro L. Rodrigues ◽  
Sandro Queiros ◽  
...  
2021 ◽  
pp. 004947552199818
Author(s):  
Ellen Wilkinson ◽  
Noel Aruparayil ◽  
J Gnanaraj ◽  
Julia Brown ◽  
David Jayne

Laparoscopic surgery has the potential to improve care in resource-deprived low- and-middle-income countries (LMICs). This study aims to analyse the barriers to training in laparoscopic surgery in LMICs. Medline, Embase, Global Health and Web of Science were searched using ‘LMIC’, ‘Laparoscopy’ and ‘Training’. Two researchers screened results with mutual agreement. Included papers were in English, focused on abdominal laparoscopy and training in LMICs. PRISMA guidelines were followed; 2992 records were screened, and 86 full-text articles reviewed to give 26 key papers. Thematic grouping identified seven key barriers: funding; availability and maintenance of equipment; local access to experienced laparoscopic trainers; stakeholder dynamics; lack of knowledge on effective training curricula; surgical departmental structure and practical opportunities for trainees. In low-resource settings, technological advances may offer low-cost solutions in the successful implementation of laparoscopic training and improve access to surgical care.


2016 ◽  
Vol 14 (4) ◽  
pp. 468-472 ◽  
Author(s):  
Carla Ferreira Kikuchi Fernandes ◽  
◽  
José Maria Cordeiro Ruano ◽  
Lea Mina Kati ◽  
Alberto Sinhiti Noguti ◽  
...  

ABSTRACT Objective To evaluate laparoscopic skills of third-year Gynecology and Obstetrics residents after training at a training and surgical experimentation center. Methods Use of a prospective questionnaire analyzing demographic data, medical residency, skills, competences, and training in a box trainer and in pigs. Results After the training, there was significant improvement in laparoscopic skills according to the residents (before 1.3/after 2.7; p=0.000) and preceptors (before 2.1/after 4.8; p=0.000). There was also significant improvement in the feeling of competence in surgeries with level 1 and 2 of difficulty. All residents approved the training. Conclusion The training was distributed into 12 hours in the box trainer and 20 hours in animals, and led to better laparoscopic skills and a feeling of more surgical competence in laparoscopic surgery levels 1 and 2.


2009 ◽  
Vol 18 (3) ◽  
pp. 242-246 ◽  
Author(s):  
Hiten R.H. Patel ◽  
Ana Linares ◽  
Jean V. Joseph

2011 ◽  
Vol 285 (1) ◽  
pp. 155-160 ◽  
Author(s):  
Cristiano Rossitto ◽  
Maria Lucia Gagliardi ◽  
Anna Fagotti ◽  
Francesco Fanfani ◽  
Valerio Gallotta ◽  
...  

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Paul Maria Scheikl ◽  
Stefan Laschewski ◽  
Anna Kisilenko ◽  
Tornike Davitashvili ◽  
Benjamin Müller ◽  
...  

AbstractSemantic segmentation of organs and tissue types is an important sub-problem in image based scene understanding for laparoscopic surgery and is a prerequisite for context-aware assistance and cognitive robotics. Deep Learning (DL) approaches are prominently applied to segmentation and tracking of laparoscopic instruments. This work compares different combinations of neural networks, loss functions, and training strategies in their application to semantic segmentation of different organs and tissue types in human laparoscopic images in order to investigate their applicability as components in cognitive systems. TernausNet-11 trained on Soft-Jaccard loss with a pretrained, trainable encoder performs best in regard to segmentation quality (78.31% mean Intersection over Union [IoU]) and inference time (28.07 ms) on a single GTX 1070 GPU.


2015 ◽  
Vol 31 (4) ◽  
pp. 392-400 ◽  
Author(s):  
Kelli Gruber ◽  
Amr S. Soliman ◽  
Kendra Schmid ◽  
Bryan Rettig ◽  
June Ryan ◽  
...  

2005 ◽  
Vol 47 (3) ◽  
pp. 346-351 ◽  
Author(s):  
M.P. Laguna ◽  
L.C. Schreuders ◽  
J.J. Rassweiler ◽  
C.C. Abbou ◽  
R. van Velthoven ◽  
...  

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