Lukas Heine
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View article: Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation
Learning to Look Closer: A New Instance-Wise Loss for Small Cerebral Lesion Segmentation Open
Traditional loss functions in medical image segmentation, such as Dice, often under-segment small lesions because their small relative volume contributes negligibly to the overall loss. To address this, instance-wise loss functions and met…
View article: Automated measurement of macular neovascularization lesion size in nAMD using AI segmentation
Automated measurement of macular neovascularization lesion size in nAMD using AI segmentation Open
Purpose To compare artificial intelligence (AI)-based annotations of hyperreflective material (HRM) and manual demarcation of macular neovascularization (MNV) on optical coherence tomography (OCT) volume scans in neovascular age-related ma…
View article: Automated measurement of macular neovascularization lesion size in nAMD using AI segmentation
Automated measurement of macular neovascularization lesion size in nAMD using AI segmentation Open
Purpose To compare artificial intelligence (AI)-based annotations of hyperreflective material (HRM) and manual demarcation of macular neovascularization (MNV) on optical coherence tomography (OCT) volume scans in neovascular age-related ma…
View article: LiMeTrack: A lightweight biosample management platform for the multicenter SATURN3 consortium
LiMeTrack: A lightweight biosample management platform for the multicenter SATURN3 consortium Open
Biomedical research projects involving large patient cohorts are increasingly complex, both in terms of data modalities and number of samples. Such projects require robust data management solutions to foster data integrity, reproducibility…
View article: Three-Dimensional Quantification of Macular OCT Alterations Improves the Diagnostic Performance of Artificial Intelligence Models
Three-Dimensional Quantification of Macular OCT Alterations Improves the Diagnostic Performance of Artificial Intelligence Models Open
The presented approach can streamline clinical workflows by reducing the time and effort required for manual annotations, ultimately supporting more efficient and accurate monitoring of AMD progression and treatment response. We provide op…
View article: De-identification of medical imaging data: a comprehensive tool for ensuring patient privacy
De-identification of medical imaging data: a comprehensive tool for ensuring patient privacy Open
Objectives Medical imaging data employed in research frequently comprises sensitive Protected Health Information (PHI) and Personal Identifiable Information (PII), which is subject to rigorous legal frameworks such as the General Data Prot…
View article: Foreign object segmentation in chest x-rays through anatomy-guided shape insertion
Foreign object segmentation in chest x-rays through anatomy-guided shape insertion Open
In this paper, we tackle the challenge of instance segmentation for foreign objects in chest radiographs, commonly seen in postoperative follow-ups with stents, pacemakers, or ingested objects in children. The diversity of foreign objects …
View article: CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models
CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models Open
Digital Pathology is a cornerstone in the diagnosis and treatment of diseases. A key task in this field is the identification and segmentation of cells in hematoxylin and eosin-stained images. Existing methods for cell segmentation often r…
View article: De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy
De-Identification of Medical Imaging Data: A Comprehensive Tool for Ensuring Patient Privacy Open
Medical data employed in research frequently comprises sensitive patient health information (PHI), which is subject to rigorous legal frameworks such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and …
View article: Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data
Spacewalker: Traversing Representation Spaces for Fast Interactive Exploration and Annotation of Unstructured Data Open
In industries such as healthcare, finance, and manufacturing, analysis of unstructured textual data presents significant challenges for analysis and decision making. Uncovering patterns within large-scale corpora and understanding their se…
View article: Anatomy-guided Pathology Segmentation
Anatomy-guided Pathology Segmentation Open
Pathological structures in medical images are typically deviations from the expected anatomy of a patient. While clinicians consider this interplay between anatomy and pathology, recent deep learning algorithms specialize in recognizing ei…
View article: CellViT: Vision Transformers for precise cell segmentation and classification
CellViT: Vision Transformers for precise cell segmentation and classification Open
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and siz…
View article: CellViT: Vision Transformers for Precise Cell Segmentation and Classification
CellViT: Vision Transformers for Precise Cell Segmentation and Classification Open
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images are important clinical tasks and crucial for a wide range of applications. However, it is a challenging task due to nuclei variances in staining and siz…
View article: MedShapeNetCore
MedShapeNetCore Open
MedShapeNetCore is a subset of MedShapeNet, containing more lightweight 3D anatomical shapes in the format of mask, point cloud and mesh. The shape data are stored as numpy arrays in nested dictonaries in npz format (Zenodo). This API prov…
View article: Conversational Agents for Mental Health and Well-being: Discovering Design Recommendations Using Text Mining
Conversational Agents for Mental Health and Well-being: Discovering Design Recommendations Using Text Mining Open
Conversational agents are increasingly being used by the general population due to shortages in healthcare providers and specialists, and limited access to treatments. They are also used by people to deal with loneliness and lack of compan…