# Daichi Kitaguchi

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/daichi-kitaguchi/

## Facts

| Field | Value |
| --- | --- |
| Citations | 1,498 |
| Field | Colorectal Cancer Surgical Treatments |
| h-index | 22 |
| i10-index | 34 |
| Last Known Institution | University of Tsukuba |
| OpenAlex ID | https://openalex.org/A5083112074 |
| ORCID iD | 0000-0002-8197-6317 |
| Works | 106 |

## Researcher papers

- [Real-time automatic surgical phase recognition in laparoscopic sigmoidectomy using the convolutional neural network-based deep learning approach](https://scholariq.org/papers/real-time-automatic-surgical-phase-recognition-in-laparoscopic-sigmoidectomy/)
- [Automated laparoscopic colorectal surgery workflow recognition using artificial intelligence: Experimental research](https://scholariq.org/papers/automated-laparoscopic-colorectal-surgery-workflow-recognition-using-artificial/)
- [Artificial intelligence‐based computer vision in surgery: Recent advances and future perspectives](https://scholariq.org/papers/artificial-intelligence-based-computer-vision-in-surgery-recent-advances-and/)
- [Automatic Surgical Skill Assessment System Based on Concordance of Standardized Surgical Field Development Using Artificial Intelligence](https://scholariq.org/papers/automatic-surgical-skill-assessment-system-based-on-concordance-of-standardized/)
- [Development and Validation of a 3-Dimensional Convolutional Neural Network for Automatic Surgical Skill Assessment Based on Spatiotemporal Video Analysis](https://scholariq.org/papers/development-and-validation-of-a-3-dimensional-convolutional-neural-network-for/)
- [Computer-assisted real-time automatic prostate segmentation during TaTME: a single-center feasibility study](https://scholariq.org/papers/computer-assisted-real-time-automatic-prostate-segmentation-during-tatme-a/)
- [Deep learning-based automatic surgical step recognition in intraoperative videos for transanal total mesorectal excision](https://scholariq.org/papers/deep-learning-based-automatic-surgical-step-recognition-in-intraoperative-videos/)
- [Real-time vascular anatomical image navigation for laparoscopic surgery: experimental study](https://scholariq.org/papers/real-time-vascular-anatomical-image-navigation-for-laparoscopic-surgery/)
- [Deep-learning-based semantic segmentation of autonomic nerves from laparoscopic images of colorectal surgery: an experimental pilot study](https://scholariq.org/papers/deep-learning-based-semantic-segmentation-of-autonomic-nerves-from-laparoscopic/)
- [Artificial intelligence for the recognition of key anatomical structures in laparoscopic colorectal surgery](https://scholariq.org/papers/artificial-intelligence-for-the-recognition-of-key-anatomical-structures-in/)
- [Artificial intelligence assessment of tissue-dissection efficiency in laparoscopic colorectal surgery](https://scholariq.org/papers/artificial-intelligence-assessment-of-tissue-dissection-efficiency-in/)
- [Objective surgical skill assessment based on automatic recognition of dissection and exposure times in robot-assisted radical prostatectomy](https://scholariq.org/papers/objective-surgical-skill-assessment-based-on-automatic-recognition-of-dissection/)

## Researcher topics

- [Colorectal Cancer Surgical Treatments](https://scholariq.org/topics/colorectal-cancer-surgical-treatments/)
- [Surgical Simulation and Training](https://scholariq.org/topics/surgical-simulation-and-training/)
- [Anorectal Disease Treatments and Outcomes](https://scholariq.org/topics/anorectal-disease-treatments-and-outcomes/)
- [Colorectal and Anal Carcinomas](https://scholariq.org/topics/colorectal-and-anal-carcinomas/)
- [Colorectal Cancer Screening and Detection](https://scholariq.org/topics/colorectal-cancer-screening-and-detection/)

## Researcher university

- [University of Tsukuba](https://scholariq.org/institutions/university-of-tsukuba/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.