activity
20192025
most citedSimCol3D -- 3D Reconstruction during Colonoscopy Challenge

25 citations · 28 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2025

A Statistical 3D Stomach Shape Model for Anatomical Analysis

Erez Posner, Ore Shtalrid, Oded Erell +2

Realistic and parameterized 3D models of human anatomy have become invaluable in research, diagnostics, and surgical planning. However, the development of detailed models for inter…

cs.CV2023★ 25 cited

SimCol3D -- 3D Reconstruction during Colonoscopy Challenge

Anita Rau, Sophia Bano, Yueming Jin +19

Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps…

cs.CV2023

ColNav: Real-Time Colon Navigation for Colonoscopy

Netanel Frank, Erez Posner, Emmanuelle Muhlethaler +2

Colorectal cancer screening through colonoscopy continues to be the dominant global standard, as it allows identifying pre-cancerous or adenomatous lesions and provides the ability…

cs.CV2022

Estimating the coverage in 3d reconstructions of the colon from colonoscopy videos

Emmanuelle Muhlethaler, Erez Posner, Moshe Bouhnik

Colonoscopy is the most common procedure for early detection and removal of polyps, a critical component of colorectal cancer prevention. Insufficient visual coverage of the colon…

cs.CV2022

Colonoscopy Landmark Detection using Vision Transformers

Aniruddha Tamhane, Tse'ela Mida, Erez Posner +1

Colonoscopy is a routine outpatient procedure used to examine the colon and rectum for any abnormalities including polyps, diverticula and narrowing of colon structures. A signific…

cs.CV2022★ 3 cited

CFusion: Consistent Contrastive Colon Fusion, Towards Deep SLAM in Colonoscopy

Erez Posner, Adi Zholkover, Netanel Frank +1

3D colon reconstruction from Optical Colonoscopy (OC) to detect non-examined surfaces remains an unsolved problem. The challenges arise from the nature of optical colonoscopy data,…

cs.CV2019

Motion Segmentation Using Locally Affine Atom Voting

Erez Posner, Rami Hagege

We present a novel method for motion segmentation called LAAV (Locally Affine Atom Voting). Our model's main novelty is using sets of features to segment motion for all features in…