Hiroki Matsuzaki

Feasibility of a Stool State Check App Using AI During Bowel Preparation Before Colonoscopy: Multicenter Prospective Study (SCAN Study)

Atsushi Inaba, Kensuke Shinmura, Shozo Osera, Takahiro Yamada et autres

Background: Optimal bowel preparation (BP) is crucial for a successful colonoscopy. Although multiple factors influence BP quality, including patient adherence to laxatives and dietary instructions, the stool state during BP should be properly evaluated to perform a colonoscopy of sufficient quality. Therefore, …

jp (code pays fourni par la source)

Cholec80-port: A Geometrically Consistent Trocar Port Segmentation Dataset for Robust Surgical Scene Understanding

Shunsuke Kikuchi, Atsushi Kouno, Hiroki Matsuzaki

Trocar ports are camera-fixed, pseudo-static structures that can persistently occlude laparoscopic views and attract disproportionate feature points due to specular, textured surfaces. This makes ports particularly detrimental to geometry-based downstream pipelines such as image stitching, 3D reconstruction, and visual SLAM, where dynamic …

Cholec80-port: A Geometrically Consistent Trocar Port Segmentation Dataset for Robust Surgical Scene Understanding

Shunsuke Kikuchi, Atsushi Kouno, Hiroki Matsuzaki

Trocar ports are camera-fixed, pseudo-static structures that can persistently occlude laparoscopic views and attract disproportionate feature points due to specular, textured surfaces. This makes ports particularly detrimental to geometry-based downstream pipelines such as image stitching, 3D reconstruction, and visual SLAM, where dynamic …

jp (code pays fourni par la source)

Semantic segmentation deep learning model boosts surgeons’ organ recognition in minimally invasive hysterectomy – a prospective multi-center reader performance study using pre-selected video clips

Shin Takenaka, Hiroki Matsuzaki, Yusuke Hirose, Makoto Nakabayashi et autres

BACKGROUND: Injury to the ureter and bladder during minimally invasive hysterectomy remains a serious complication, often resulting from insufficient intraoperative organ recognition. Artificial intelligence (AI)-based support systems may improve anatomical recognition and reduce such risks. We aimed to evaluate whether an AI-based …

jp (code pays fourni par la source)

Deep learning-based vessel and nerve recognition model for lateral lymph node dissection: a retrospective feasibility study

Shoma Sasaki, Daichi Kitaguchi, Tomohiro Noda, Hiroki Matsuzaki et autres

PURPOSE: Lateral lymph node dissection for rectal cancer is challenging because of the presence of blood vessels and nerves essential for postoperative genitourinary function and leg movements. Identifying these structures during surgery is crucial. We developed a deep learning-based semantic segmentation model …

jp (code pays fourni par la source)

Construction of a Feedback Comment Analysis Model for Evaluation of Endoscopic Surgical Skill

Shin Takenaka, Daichi Kitaguchi, Hiroki Matsuzaki, Kei Nakajima et autres

Background: Surgical education and skill assessments are important in improving surgical skills. However, instructors' comments tend to be complex and unorganized, with varying content and categories. This study aimed to develop a natural language processing (NLP) model to automatically classify feedback comments …

jp (code pays fourni par la source)

Surgical step recognition in laparoscopic distal gastrectomy using artificial intelligence: a proof-of-concept study

Mitsumasa Yoshida, Daichi Kitaguchi, Nobuyoshi Takeshita, Hiroki Matsuzaki et autres

jp (code pays fourni par la source)

Smartphone application for artificial intelligence‐based evaluation of stool state during bowel preparation before colonoscopy

Atsushi Inaba, Kensuke Shinmura, Hiroki Matsuzaki, Nobuyoshi Takeshita et autres

OBJECTIVES: Colonoscopy (CS) is an important screening method for the early detection and removal of precancerous lesions. The stool state during bowel preparation (BP) should be properly evaluated to perform CS with sufficient quality. This study aimed to develop a smartphone application …

jp (code pays fourni par la source)

SurgT challenge: Benchmark of soft-tissue trackers for robotic surgery

João Cartucho, Alistair Weld, Samyakh Tukra, Haozheng Xu et autres

gb, kr, ca, de, pt (code pays fourni par la source)

Automatic Surgical Skill Assessment System Based on Concordance of Standardized Surgical Field Development Using Artificial Intelligence

Takahiro Igaki, Daichi Kitaguchi, Hiroki Matsuzaki, Kei Nakajima et autres

Importance: Automatic surgical skill assessment with artificial intelligence (AI) is more objective than manual video review-based skill assessment and can reduce human burden. Standardization of surgical field development is an important aspect of this skill assessment. Objective: To develop a deep learning …

jp (code pays fourni par la source)

PEg TRAnsfer Workflow recognition challenge report: Do multimodal data improve recognition?

Arnaud Huaulmé, Kanako Harada, Quang-Minh Nguyen, Bogyu Park et autres

fr, jp, us, cn, hk, in, sg (code pays fourni par la source)

SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic Surgery

João Cartucho, Alistair Weld, Samyakh Tukra, Haozheng Xu et autres

This paper introduces the ``SurgT: Surgical Tracking" challenge which was organised in conjunction with MICCAI 2022. There were two purposes for the creation of this challenge: (1) the establishment of the first standardised benchmark for the research community to assess soft-tissue trackers; …