Feasibility of optical stereotactic navigation for rectosigmoid cancer with deep learning-supported 3D modelling

Authors

Institutions

Publication Details

Journal
European Journal of Surgical Oncology
Published
2025-08-25
DOI
https://doi.org/10.1016/j.ejso.2025.110397
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Feasibility of optical stereotactic navigation for rectosigmoid cancer with deep learning-supported 3D modelling

Paul C. Jutte, Can Ozan Tan, Thomas C. Kwee, Gürsah Kats‐Ugurlu et al.
1 citations
European Journal of Surgical Oncology
Radiomics and Machine Learning in Medical Imaging
1.36
article

Feasibility of optical stereotactic navigation for rectosigmoid cancer with deep learning-supported 3D modelling

Paul C. Jutte, Can Ozan Tan, Thomas C. Kwee, Gürsah Kats‐Ugurlu, A. R. Wijsmuller, Klaas Havenga, Patrick Hemmer, Joep Kraeima, Jean Paul de Vries, Reinier ten Brink, Renske Schram
article en
1 citations

Abstract

No abstract available for this paper.
European Journal of Surgical OncologyVol. 51(11)
University Medical Center Groningen (NL), University of Groningen (NL), University of Twente (NL)
Openalex Percentile: Top 16%
Radiomics and Machine Learning in Medical Imaging
1.36
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.