Michael Baumgartner
A5101474595- Radiomics and Machine Learning in Medical Imaging
- Advanced Neural Network Applications
- AI in cancer detection
- Water Quality Monitoring and Analysis
- Analytical Chemistry and Sensors
- COVID-19 diagnosis using AI
- Advanced Chemical Sensor Technologies
- Artificial Intelligence in Healthcare and Education
- Edible Oils Quality and Analysis
- Explainable Artificial Intelligence (XAI)
- Spectroscopy and Chemometric Analyses
- Non-Invasive Vital Sign Monitoring
- Machine Learning and Data Classification
- Cerebrovascular and Carotid Artery Diseases
- Prostate Cancer Diagnosis and Treatment
- Medical Imaging and Analysis
- Integrated Circuits and Semiconductor Failure Analysis
- History and Developments in Astronomy
- Adversarial Robustness in Machine Learning
- Biomedical and Engineering Education
- Electrochemical sensors and biosensors
- Lung Cancer Diagnosis and Treatment
- Electron and X-Ray Spectroscopy Techniques
- Healthcare Technology and Patient Monitoring
- Teaching and Learning Programming
German Cancer Research Center
2021-2025
Heidelberg University
2021-2025
ETH Zurich
2024
DKFZ-ZMBH Alliance
2024
University of Pennsylvania
2023
ZHAW Zurich University of Applied Sciences
2018-2021
Western Michigan University
2020-2021
Stryker (United States)
2020-2021
RWTH Aachen University
2019
Mintek
2019
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,...
Accurate detection and quantification of unruptured intracranial aneurysms (UIAs) is important for rupture risk assessment to allow an informed treatment decision be made. Currently, 2D manual measures used assess UIAs on Time-of-Flight magnetic resonance angiographies (TOF-MRAs) lack 3D information there substantial inter-observer variability both aneurysm size growth. could helpful improve but are time-consuming would therefore benefit from a reliable automatic UIA segmentation method. The...
Breast cancer is one of the most common causes death among women worldwide. Early detection helps in reducing number deaths. Automated 3D Ultrasound (ABUS) a newer approach for breast screening, which has many advantages over handheld mammography such as safety, speed, and higher rate cancer. Tumor detection, segmentation, classification are key components analysis medical images, especially challenging context ABUS due to significant variability tumor size shape, unclear boundaries, low...
Increasing evidence shows that flaws in machine learning (ML) algorithm validation are an underestimated global problem. Particularly automatic biomedical image analysis, chosen performance metrics often do not reflect the domain interest, thus failing to adequately measure scientific progress and hindering translation of ML techniques into practice. To overcome this, our large international expert consortium created Metrics Reloaded, a comprehensive framework guiding researchers...
Abstract Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute ischemic stroke (AIS), computer-aided (CAD) systems can accelerate underlying diagnostic processes. Here, we developed an artificial neural network (ANN) which allows automated detection abnormal vessel findings without any a-priori restrictions <2 minutes. Pseudo-prospective external validation was performed consecutive suspected AIS from 4 different hospitals during 6-month...
The release of nnU-Net marked a paradigm shift in 3D medical image segmentation, demonstrating that properly configured U-Net architecture could still achieve state-of-the-art results. Despite this, the pursuit novel architectures, and respective claims superior performance over baseline, continued. In this study, we demonstrate many these recent fail to hold up when scrutinized for common validation shortcomings, such as use inadequate baselines, insufficient datasets, neglected...
Abstract Background Gadolinium-enhanced “sampling perfection with application-optimized contrasts using different flip angle evolution” (SPACE) sequence allows better visualization of brain metastases (BMs) compared to “magnetization-prepared rapid acquisition gradient echo” (MPRAGE). We hypothesize that this conspicuity leads high-quality annotation (HAQ), enhancing deep learning (DL) algorithm detection BMs on MPRAGE images. Methods Retrospective contrast-enhanced (gadobutrol 0.1 mmol/kg)...
Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments patients with aortic dissections. However, existing methods reduce to a binary problem, limiting their ability measure diameters across different branches zones. Furthermore, no open-source dataset currently available support development multi-class methods. To address this gap, we organized AortaSeg24 MICCAI Challenge, introducing...
INTRODUCTION: Hemispherotomy represents definitive treatment for drug-resistant epilepsy with unilateral hemispheric onset. Traditional approaches involve a large incision and open craniotomy, associated risks of blood loss, infection, poor wound healing, pain, cosmetic concerns, long hospital stays. The authors describe minimally invasive technique performing hemispherotomy through single burr hole overlying the Sylvian fissure. METHODS: A retrospective analysis was performed on first seven...
Extra virgin olive oil (EVOO) is the highest quality of and characterized by highly beneficial nutritional properties. The large increase in both consumption fraud, for example through adulteration, creates new challenges an increasing demand developing assessment methodologies that are easier cheaper to perform. As today, determination performed producers chemical analysis organoleptic evaluation. requires advanced equipment knowledge certified laboratories, has therefore limited...
Accurate detection and tracking of surrounding objects is essential to enable self-driving vehicles. While Light Detection Ranging (LiDAR) sensors have set the benchmark for high performance, appeal camera-only solutions lies in their cost-effectiveness. Notably, despite prevalent use Radio (RADAR) automotive systems, potential 3D has been largely disregarded due data sparsity measurement noise. As a recent development, combination RADARs cameras emerging as promising solution. This paper...
Abstract Objectives To develop and test a Retina U-Net algorithm for the detection of primary lung tumors associated metastases all stages on FDG-PET/CT. Methods A data set consisting 364 FDG-PET/CTs patients with histologically confirmed cancer was used development internal testing. The comprised stages. All (T), lymphatic (N), distant (M) were manually segmented as 3D volumes using whole-body PET/CT series. split into training ( n = 216), validation 74), 74). Detection performance lesion...
While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment validation used algorithms, but relatively little attention has been given practical pitfalls when using specific a task. These typically related (1) disregard inherent metric properties, such as behaviour in presence class...
Phosphors based on magnesium titanate activated with Mn 4 + ions are of great interest because, when excited blue light, they display a strong red-emitting luminescence. They characterized by luminescence decay which is strongly temperature dependent in the range from -50 ∘ C to 150 C, making these materials very promising for sensing biochemical field. In this work, optical and thermal properties Mg 2 TiO investigated different doping concentrations. The potential material demonstrated...
Validation metrics are key for the reliable tracking of scientific progress and bridging current chasm between artificial intelligence (AI) research its translation into practice. However, increasing evidence shows that particularly in image analysis, often chosen inadequately relation to underlying problem. This could be attributed a lack accessibility metric-related knowledge: While taking account individual strengths, weaknesses, limitations validation is critical prerequisite making...