Lena Maier‐Hein
A5023493127- Photoacoustic and Ultrasonic Imaging
- Optical Imaging and Spectroscopy Techniques
- Surgical Simulation and Training
- Radiomics and Machine Learning in Medical Imaging
- Artificial Intelligence in Healthcare and Education
- Augmented Reality Applications
- Anatomy and Medical Technology
- Robotics and Sensor-Based Localization
- Soft Robotics and Applications
- Thermography and Photoacoustic Techniques
- Medical Image Segmentation Techniques
- Colorectal Cancer Screening and Detection
- Advanced Radiotherapy Techniques
- AI in cancer detection
- Advanced Neural Network Applications
- Infrared Thermography in Medicine
- Ultrasound Imaging and Elastography
- 3D Shape Modeling and Analysis
- Medical Imaging Techniques and Applications
- Optical Coherence Tomography Applications
- Biomedical Text Mining and Ontologies
- 3D Surveying and Cultural Heritage
- Advanced X-ray and CT Imaging
- Advanced Optical Sensing Technologies
- Advanced Vision and Imaging
German Cancer Research Center
2016-2025
Heidelberg University
2016-2025
National Center for Tumor Diseases
2023-2025
DKFZ-ZMBH Alliance
2015-2024
University Hospital Heidelberg
2018-2024
Nationales Centrum für Tumorerkrankungen Dresden
2024
Carl von Ossietzky Universität Oldenburg
2023
Diakonie-Klinikum Stuttgart
2023
Klinikum Stuttgart
2023
University of Cambridge
2022
International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far most widely investigated medical processing task, but various segmentation typically been organized in isolation, such that algorithm development was driven by need to tackle single clinical problem. We hypothesized method capable performing well on multiple tasks will generalize previously unseen task and potentially outperform...
Semantic segmentation of medical images aims to associate a pixel with label in image without human initialization. The success semantic algorithms is contingent on the availability high-quality imaging data corresponding labels provided by experts. We sought create large collection annotated datasets various clinically relevant anatomies available under open source license facilitate development algorithms. Such resource would allow: 1) objective assessment general-purpose methods through...
Colonoscopy is the gold standard for colon cancer screening though some polyps are still missed, thus preventing early disease detection and treatment. Several computational systems have been proposed to assist polyp during colonoscopy but so far without consistent evaluation. The lack of publicly available annotated databases has made it difficult compare methods assess if they achieve performance levels acceptable clinical use. Automatic Polyp Detection sub-challenge, conducted as part...
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting recommendations studies developing or evaluating performance model. Methodological advances field have since included widespread use artificial intelligence (AI) powered by machine learning methods develop models. An update is thus needed. TRIPOD+AI provides harmonised guidance studies, irrespective whether regression...
International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical common practices related to organization has not yet been performed. In this paper, we present comprehensive conducted up now. We demonstrate importance and show lack quality control consequences. First, reproducibility interpretation results often hampered as only fraction relevant information typically provided. Second, rank...
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications AI in healthcare have the potential to improve our ability detect, diagnose, prognose, and intervene on human disease. For models be used clinically, they need made safe, reproducible robust, underlying software framework must aware particularities (e.g. geometry, physiology, physics) medical data being processed. This work introduces MONAI, freely available, community-supported,...
Even though radiomics can hold great potential for supporting clinical decision-making, its current use is mostly limited to academic research, without applications in routine practice. The workflow of complex due several methodological steps and nuances, which often leads inadequate reporting evaluation, poor reproducibility. Available guidelines checklists artificial intelligence predictive modeling include relevant good practices, but they are not tailored radiomic research. There a clear...
Abstract Biomedical image analysis algorithm validation depends on high-quality annotation of reference datasets, for which labelling instructions are key. Despite their importance, optimization remains largely unexplored. Here we present a systematic study and impact quality in the field. Through comprehensive examination professional practice international competitions registered at Medical Image Computing Computer Assisted Intervention Society, largest society biomedical imaging field,...
Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase safety operation through context-sensitive warnings semi-autonomous robotic or improve training surgeons via data-driven feedback. In up to 91% average precision has been reported phase recognition on an open data single-center video dataset. this work we investigated generalizability algorithms in a multicenter setting including more...
Since its introduction in the early 1990s, Iterative Closest Point (ICP) algorithm has become one of most well-known methods for geometric alignment 3D models. Given two roughly aligned shapes represented by point sets, iteratively establishes correspondences given current data and computes a rigid transformation accordingly. From statistical view, however, it implicitly assumes that points are observed with isotropic Gaussian noise. In this paper, we show assumption may lead to errors...
Intra-operative imaging techniques for obtaining the shape and morphology of soft-tissue surfaces in vivo are a key enabling technology advanced surgical systems. Different optical 3-D surface reconstruction laparoscopy have been proposed, however, so far no quantitative comparative validation has performed. Furthermore, robustness methods to clinically important factors like smoke or bleeding not yet assessed. To address these issues, we formed joint international initiative with aim...
In 2015 we began a sub-challenge at the EndoVis workshop MICCAI in Munich using endoscope images of ex-vivo tissue with automatically generated annotations from robot forward kinematics and instrument CAD models. However, limited background variation simple motion rendered dataset uninformative learning about which techniques would be suitable for segmentation real surgery. 2017, same Quebec introduced robotic 10 teams participating challenge to perform binary, articulating parts type da...