Publications by authors named "Yuriko Harai"
Article Synopsis
- The study focused on creating a deep learning model to automatically identify major blood vessels during laparoscopic right hemicolectomy (RHC) for colon cancer, which is crucial for safe surgery and lymph node removal.
- A total of 2624 images from laparoscopic procedures were analyzed, with the model showing the best accuracy in recognizing the superior mesenteric vein, while the ileocolic artery and vein had lower accuracy ratings.
- Surgeons rated the model positively for clinical application, suggesting it could help improve navigation and visualization of blood vessels during surgeries.
PEg TRAnsfer Workflow recognition challenge report: Do multimodal data improve recognition?
Comput Methods Programs Biomed
June 2023
Background And Objective: In order to be context-aware, computer-assisted surgical systems require accurate, real-time automatic surgical workflow recognition. In the past several years, surgical video has been the most commonly-used modality for surgical workflow recognition. But with the democratization of robot-assisted surgery, new modalities, such as kinematics, are now accessible.
View Article and Find Full Text PDFBackground: The preservation of autonomic nerves is the most important factor in maintaining genitourinary function in colorectal surgery; however, these nerves are not clearly recognisable, and their identification is strongly affected by the surgical ability. Therefore, this study aimed to develop a deep learning model for the semantic segmentation of autonomic nerves during laparoscopic colorectal surgery and to experimentally verify the model through intraoperative use and pathological examination.
Materials And Methods: The annotation data set comprised videos of laparoscopic colorectal surgery.