Detail page

Knowledge Web

Person

Christoph Palm (1971-)

Informatiker

Name	Christoph Palm
Time	1971- (Date of birth and death)
Place	Deutschland
Gender	männlich
Academic degree	Prof. Dr. rer. nat.
Profession	Informatiker (characteristic profession)
Variant	Christoph Arnold Palm
Related	Ostbayerische Technische Hochschule Regensburg. Fakultät Informatik und Mathematik (2010-)
Further information	Diss., Fakultät für Mathematik, Informatik und Naturwissenschaften
Source	https://re-mic.de/leitung (Stand: 28.11.2025)
Record type	Person
GND-Identifier	124964494
Record ID	124964494
Involved in show all Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026 Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026 Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos Enhancing generalization in zero-shot multi-label endoscopic instrument classification TransConv: a lightweight architecture based on transformers and convolutional neural networks for adenocarcinoma and Barrett’s esophagus identification Artificial intelligence improves submucosal vessel detection during third space endoscopy Evaluating smartphone-based 3D imaging techniques for clinical application in oral and maxillofacial surgery: A comparative study with the vectra M5 Reply to Tyagi et al. Bildverarbeitung für die Medizin 2025 : proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 Bildverarbeitung für die Medizin 2025 : Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 Retraction Note: Learning visual representations with optimum-path forest and its applications to Barrett’s esophagus and adenocarcinoma diagnosis Layer-selective deep representation to improve esophageal cancer classification Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial DeepCraftFuse: visual and deeply-learnable features work better together for esophageal cancer detection in patients with Barrett’s esophagus Bildverarbeitung für die Medizin 2024 : proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 Bildverarbeitung für die Medizin 2024 : Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 Corrigendum to “Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art” [Comput. Biol. Med. 169 (2024) 107929] Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art Utility of Smartphone-based Three-dimensional Surface Imaging for Digital Facial Anthropometry Bildverarbeitung für die Medizin 2023 : proceedings, German Workshop on Medical Image Computing, Braunschweig, July 2-4, 2023 Bildverarbeitung für die Medizin 2023 : Proceedings, German Workshop on Medical Image Computing, Braunschweig, July 2-4, 2023 Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans 2018 Robotic Scene Segmentation Challenge An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis Bildverarbeitung für die Medizin 2022 : proceedings, German workshop on medical image computing, Heidelberg, June 26-28, 2022 Bildverarbeitung für die Medizin 2022 : Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022 Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm Multimodal imaging for detection and segmentation of Barrett’s esophagus-related neoplasia using artificial intelligence IJCARS: BVM 2021 special issue Correction to: New aspects in digital breast assessment: further refinement of a method for automated digital anthropometry Bildverarbeitung für die Medizin 2021 : proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021 Bildverarbeitung für die Medizin 2021 : Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021 Convolutional Neural Networks for the evaluation of cancer in Barrett’s esophagus: Explainable AI to lighten up the black-box IJCARS: BVM 2021 special issue New aspects in digital breast assessment: further refinement of a method for automated digital anthropometry A Novel Method of Outcome Assessment in Breast Reconstruction Surgery: Comparison of Autologous and Alloplastic Techniques Using Three-Dimensional Surface Imaging Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study Bildverarbeitung für die Medizin 2020 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin Bildverarbeitung für die Medizin 2020 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin Real-time use of artificial intelligence in the evaluation of cancer in Barrett's oesophagus IJCARS: BVM 2019 special issue Learning visual representations with optimum-path forest and its applications to Barrett’s esophagus and adenocarcinoma diagnosis Guest editorial of the IJCARS—BVM 2018 special issue Forschung 2019 A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology Bildverarbeitung für die Medizin 2019 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 17. bis 19. März 2019 in Lübeck Bildverarbeitung für die Medizin 2019 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 17. bis 19. März 2019 in Lübeck Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma Bildverarbeitung für die Medizin 2018 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen Bildverarbeitung für die Medizin 2018 : Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg 2017 Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg 2016 Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg 2012

Please note

The beta version does not yet contain all functions and information of the DNB portal catalogue. If you are missing information or want to order a medium, please visit the page in the DNB portal catalogue via the following link:

Katalog der Deutschen Nationalbibliothek

Christoph Palm (1971-)

Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026

Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026

Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos

Enhancing generalization in zero-shot multi-label endoscopic instrument classification

TransConv: a lightweight architecture based on transformers and convolutional neural networks for adenocarcinoma and Barrett’s esophagus identification

Artificial intelligence improves submucosal vessel detection during third space endoscopy

Evaluating smartphone-based 3D imaging techniques for clinical application in oral and maxillofacial surgery: A comparative study with the vectra M5

Reply to Tyagi et al.

Bildverarbeitung für die Medizin 2025 : proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025

Bildverarbeitung für die Medizin 2025 : Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025

Retraction Note: Learning visual representations with optimum-path forest and its applications to Barrett’s esophagus and adenocarcinoma diagnosis

Layer-selective deep representation to improve esophageal cancer classification

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

DeepCraftFuse: visual and deeply-learnable features work better together for esophageal cancer detection in patients with Barrett’s esophagus

Bildverarbeitung für die Medizin 2024 : proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024

Bildverarbeitung für die Medizin 2024 : Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024

Corrigendum to “Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art” [Comput. Biol. Med. 169 (2024) 107929]

Influence of artificial intelligence on the diagnostic performance of endoscopists in the assessment of Barrett’s esophagus: a tandem randomized and video trial

Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art

Utility of Smartphone-based Three-dimensional Surface Imaging for Digital Facial Anthropometry

Bildverarbeitung für die Medizin 2023 : proceedings, German Workshop on Medical Image Computing, Braunschweig, July 2-4, 2023

Bildverarbeitung für die Medizin 2023 : Proceedings, German Workshop on Medical Image Computing, Braunschweig, July 2-4, 2023

Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm

Error-Correcting Mean-Teacher: Corrections instead of consistency-targets applied to semi-supervised medical image segmentation

Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans

2018 Robotic Scene Segmentation Challenge

An artificial intelligence algorithm is highly accurate for detecting endoscopic features of eosinophilic esophagitis

Bildverarbeitung für die Medizin 2022 : proceedings, German workshop on medical image computing, Heidelberg, June 26-28, 2022

Bildverarbeitung für die Medizin 2022 : Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022

Learning the shape of female breasts: an open-access 3D statistical shape model of the female breast built from 110 breast scans

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm

Multimodal imaging for detection and segmentation of Barrett’s esophagus-related neoplasia using artificial intelligence

IJCARS: BVM 2021 special issue

Correction to: New aspects in digital breast assessment: further refinement of a method for automated digital anthropometry

Bildverarbeitung für die Medizin 2021 : proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021

Bildverarbeitung für die Medizin 2021 : Proceedings, German Workshop on Medical Image Computing, Regensburg, March 7-9, 2021

Convolutional Neural Networks for the evaluation of cancer in Barrett’s esophagus: Explainable AI to lighten up the black-box

IJCARS: BVM 2021 special issue

New aspects in digital breast assessment: further refinement of a method for automated digital anthropometry

A Novel Method of Outcome Assessment in Breast Reconstruction Surgery: Comparison of Autologous and Alloplastic Techniques Using Three-Dimensional Surface Imaging

Endoscopic prediction of submucosal invasion in Barrett’s cancer with the use of Artificial Intelligence: A pilot Study

Bildverarbeitung für die Medizin 2020 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin

Bildverarbeitung für die Medizin 2020 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin

Real-time use of artificial intelligence in the evaluation of cancer in Barrett's oesophagus

IJCARS: BVM 2019 special issue

Learning visual representations with optimum-path forest and its applications to Barrett’s esophagus and adenocarcinoma diagnosis

Guest editorial of the IJCARS—BVM 2018 special issue

Forschung

A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology

A technical review of artificial intelligence as applied to gastrointestinal endoscopy: clarifying the terminology

Bildverarbeitung für die Medizin 2019 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 17. bis 19. März 2019 in Lübeck

Bildverarbeitung für die Medizin 2019 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 17. bis 19. März 2019 in Lübeck

Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma

Bildverarbeitung für die Medizin 2018 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen

Bildverarbeitung für die Medizin 2018 : Algorithmen - Systeme - Anwendungen. Proceedings des Workshops vom 11. bis 13. März 2018 in Erlangen

Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma

Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg

Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg

Forschungsbericht ... / OTH, Ostbayerische Technische Hochschule Regensburg