Deep learning driven colorectal lesion detection in gastrointestinal endoscopic and pathological imaging.

Colorectal cancer has the second highest incidence of malignant tumors and is the fourth leading cause of cancer deaths in China. Early diagnosis and treatment of colorectal cancer will lead to an improvement in the 5-year survival rate, which will reduce medical costs. The current diagnostic methods for early colorectal cancer include excreta, blood, endoscopy, and computer-aided endoscopy.

Peroral traction-assisted natural orifice trans-anal flexible endoscopic rectosigmoidectomy followed by intracorporeal colorectal anastomosis in a live porcine model.

Background: Compared to traditional open surgery, laparoscopic surgery has become a standard approach for colorectal cancer due to its great superiorities including less postoperative pain, a shorter hospital stay, and better quality of life. In 2007, Whiteford reported the first natural orifice trans-anal endoscopic surgery (NOTES) sigmoidectomy using transanal endoscopic microsurgery. To date, all cases of NOTES colorectal resection have included a hybrid laparoscopic approach with the use of established rigid platforms.