Matthias Keicher


Picture of Matthias Keicher

Dipl.-Ing. (Univ.) Matthias Keicher

Informatics 16 - Chair of Computer Aided Medical Procedures (Prof. Navab)

Postal address

Postal:
Boltzmannstr. 3
85748 Garching b. München

Place of employment

Informatics 16 - Chair of Computer Aided Medical Procedures (Prof. Navab)

Work:
Boltzmannstr. 3(5613)/III
85748 Garching b. München

Research Interests

Curriculum vitae

Matthias Keicher is a senior PhD student at the Chair for Computer Aided Medical Procedures based at the IFL Lab in the hospital Klinikum rechts der Isar in Munich. He leads a research team with a focus on structured report generation and clinical applications of vision-language models funded by the DIVA project.

  • 09/2019 - current: PhD student at the Chair for Computer Aided Medical Procedures
  • 02/2019 - current: Research Manager at the Chair for Computer Aided Medical Procedures
  • 08/2016 - 12/2018: CTO and Managing Director of SurgicEye GmbH
    • Dosimetry, interventional radiology and radio-embolisation
  • 05/2015 - 07/2016: Director of Business Development, SurgicEye GmbH
    • Minimally-invasive breast cancer staging
  • 09/2013 - 04/2015: Product Manager, SurgicEye GmbH
    • Intraoperative SPECT imaging and Ultrasound fusion
  • 10/2006 - 06/2013: Mechanical Engineering and Management at TUM (Dipl.-Ing.)
    • Focus on biomedical engineering and medical devices

Connect with me on LinkedIn

Teaching

I am passionate about teaching and organize the two lectures Computer Science for Medical Students (CS4MS) and Innovation Generation in the Healthcare Domain (IGHD). Additionally, I regularly support the courses Deep Learning for Medical Applications, Project Management and Software Development for Medical Applications and Machine Learning in Medical Imaging as a tutor.

2023

  • Keicher, Matthias; Burwinkel, Hendrik; Bani-Harouni, David; Paschali, Magdalini; Czempiel, Tobias; Burian, Egon; Makowski, Marcus R; Braren, Rickmer; Navab, Nassir; Wendler, Thomas: Multimodal graph attention network for COVID-19 outcome prediction. 13 (1), 2023 more…
  • Pellegrini, Chantal; Keicher, Matthias; Özsoy, Ege; Jiraskova, Petra; Braren, Rickmer; Navab, Nassir: Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis. In: Lecture Notes in Computer Science. Springer Nature Switzerland, 2023 more…
  • Pellegrini, Chantal; Keicher, Matthias; Özsoy, Ege; Navab, Nassir: Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting. In: Lecture Notes in Computer Science. Springer Nature Switzerland, 2023 more…
  • Zellner, Tobias; Romanek, Katrin; Rabe, Christian; Schmoll, Sabrina; Geith, Stefanie; Heier, Eva-Carina; Stich, Raphael; Burwinkel, Hendrik; Keicher, Matthias; Bani-Harouni, David; Navab, Nassir; Ahmadi, Seyed-Ahmad; Eyer, Florian: ToxNet: an artificial intelligence designed for decision support for toxin prediction. 61 (1), 2023, 56-63 more…

2022

  • Bitarafan, Adeleh; Azampour, Mohammad Farid; Bakhtari, Kian; Soleymani Baghshah, Mahdieh; Keicher, Matthias; Navab, Nassir: Vol2Flow: Segment 3D Volumes Using a Sequence of Registration Flows. Medical Image Computing and Computer Assisted Intervention -- MICCAI 2022, Springer Nature Switzerland, 2022 more…
  • Zellner, Tobias; Burwinkel, Hendrik; Keicher, Matthias; Bani-Harouni, David; Navab, Nassir; Ahmadi, Seyed-Ahmad; Eyer, Florian: ToxNet 2: Judgement Day. 60 Suppl 1, 2022, 37-38 more…

2021

  • Hedderich, Dennis M.; Keicher, Matthias; Wiestler, Benedikt; Gruber, Martin J.; Burwinkel, Hendrik; Hinterwimmer, Florian; Czempiel, Tobias; Spiro, Judith E.; Pinto dos Santos, Daniel; Heim, Dominik; Zimmer, Claus; Rückert, Daniel; Kirschke, Jan S.; Navab, Nassir: AI for Doctors—A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging. Healthcare 9 (10), 2021, 1278 more…
  • Hedderich, Dennis M; Keicher, Matthias; Wiestler, Benedikt; Gruber, Martin J; Burwinkel, Hendrik; Hinterwimmer, Florian; Czempiel, Tobias; Spiro, Judith E; Pinto Dos Santos, Daniel; Heim, Dominik; Zimmer, Claus; Rückert, Daniel; Kirschke, Jan S; Navab, Nassir: AI for Doctors-A Course to Educate Medical Professionals in Artificial Intelligence for Medical Imaging. 9 (10), 2021 more…
  • Zellner, Tobias; Burwinkel, Hendrik; Keicher, Matthias; Bani-Harouni, David; Navab, Nassir; Ahmadi, Seyed-Ahmad; Eyer, Florian: Decision support for toxin prediction using artificial intelligence. 59 (6), 2021, 541-541 more…

2020

  • Czempiel, Tobias; Paschali, Magdalini; Keicher, Matthias; Simson, Walter; Feussner, Hubertus; Kim, Seong Tae; Navab, Nassir: TeCNO: Surgical Phase Recognition with Multi-stage Temporal Convolutional Networks. In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Springer International Publishing, 2020 more…
  • Elskhawy, Abdelrahman; Lisowska, Aneta; Keicher, Matthias; Henry, Joseph; Thomson, Paul; Navab, Nassir: Continual Class Incremental Learning for CT Thoracic Segmentation. In: Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning. Springer International Publishing, 2020 more…

2014

  • Okur, Asl?; Hennersperger, Christoph; Runyan, Brent; Gardiazaball, José; Keicher, Matthias; Paepke, Stefan; Wendler, Thomas; Navab, Nassir: FhSPECT-US guided needle biopsy of sentinel lymph nodes in the axilla: is it feasible? 17 (Pt 1), 2014, 577-84 more…

Student projects

Feel free to contact me if your interested in an IDP, a guided research or a thesis.

Running and past projects:

Type Title Student
Master Thesis Learning-Based Registration of Vertebral CT Scans for Monitoring Longitudinal Changes in Cancer Patients with Spine Metastasis (in collaboration with Harvard Medical School) Malika Sanhinova
Master Thesis

GRIP: Graph-Image Contrastive Pre-Training For Chest X-ray Understanding

Mohammed Kamran

Master Thesis

Domain-specific Self-Supervised Pretraining for Vertebral Body Diagnosis

Lukas Buess
Guided Research Exploring Generative Networks as Self-Supervision for Vertebral Fracture diagnosis (iMIMIC @ MICCAI 2023) Matan Atad
Master Thesis GAN-based Data Augmentation for Imbalance Problems in Body Part X-Ray Classification Festina Ismali
MLMI Explaining Medical Image Classifiers with Visual Question Answering Models Fabian Scherer, Andrei Mancu, Alaeddine Mellouli, Çağhan Köksal
Interdisciplinary Project Interpretable Vertebral Fracture Diagnosis (iMIMIC @ MICCAI 2022) Paul Engstler
MLMI CheXplaining in Style: Counterfactual Explanations for Chest X-rays using StyleGAN (IMLH @ ICML, XAI4CV @ CVPR) Matan Atad, Vitalii Dmytrenko, Yitong Li, Xinyue Zhang
Master Thesis 3D Ultrasound Compounding for Volume Estimation in Thyroid Diagnostics Lemonia Konstantinidou
Guided Research AI-based Interpretable Dementia Recognition Marcel Kollovieh
Master Thesis Disentangled Representation Learning of Medical Brain Images Using Flow Based Models Aadhithya Sanka
Master Thesis Continual Class Incremental Learning for Thoracic segmentation in CT images (DART @ MICCAI 2020) Abdelrahman Elskhawy
Bachelor Thesis Infectious Disease Modeling for COVID-19 with Increased Spatial Resolution - Investigating Opportunities for Machine Learning and Community Mobility Data (in collaboration with Johns Hopkins University) Philipp Nikutta
Bachelor Thesis Cervical Spine Segmentation and 3D Printing for Improved Patient Treatment Planning Miruna Gafencu
Bachelor Thesis Machine Learning based Clinical Decision Support System for Poison Diagnosis (MICCAI 2020) David Bani-Harouni
Master Thesis Initialization method for the registration of 3D ultrasound volumes of the thyroid gland Mina Sedra
Master Thesis Federated Learning for Medical Applications Soham Mazumder