Image Processing in Hematology
Motivation
Blood cells are formed in the bone marrow. As mature blood cells, they later fulfill numerous important tasks. In diseases such as leukemia, typical patterns change such that fewer cells finish maturing in the bone marrow and more precursors or intermediates are found. Automated recognition of the cell type of a cell and evaluation of an entire bone marrow smear in terms of the number and distribution of certain cell types would accelerate diagnosis, objectify it and open up new avenues in cancer research.
Scientific Questions
The central task is to determine the distribution of cell types in the bone marrow. This requires reliable cell detection and classification. However, besides the large number of artifacts and cell types, other typical problems of medical imaging apply to this project: the images are extremely diverse and at the same time the amount of annotated data is limited.
Theses
New theses are regularly advertised in the area of Image Processing in Hematology. In addition to the general overview, there are also numerous topics that have not yet been advertised, which will be gladly presented in a personal conversation.
Partners
- Dr. med. Martina Crysandt, Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital RWTH Aachen
- Prof. Dr. med. Tim H. Brümmendorf, Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital RWTH Aachen
- Prof. Dr. med. Peter Boor, Institute for Pathology, University Hospital RWTH Aachen
- Dr. rer. nat. Barbara Mara Klinkhammer, Institute for Pathology, University Hospital RWTH Aachen
Contact
Publications
2022
Philipp Gräbel, Julian Thull, Martina Crysandt, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Automatic Embedding Interventions for the Classification of Hematopoietic Cells
In: 26th International Conference on Pattern Recognition (ICPR)
2022
Philipp Gräbel, Julian Thull, Martina Crysandt, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Spatial Maturity Regression for the Classification of Hematopoietic Cells
In: IEEE International Conference on Image Processing Theory and Tools and Applications (IPTA)
2022
Philipp Gräbel, Julian Thull, Martina Crysandt, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Analysis of automatically generated embedding guides for cell classification
In: IEEE International Conference on Image Processing Theory and Tools and Applications (IPTA)
2022
Philipp Gräbel, Martina Crysandt, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Ordinal classification and regression techniques for distinguishing neutrophilic cell maturity stages in human bone marrow
In: International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI)
2021
Philipp Gräbel, Özcan Özkan, Martina Crysandt, Reinhild Herwartz, Melanie Bauman, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
State of the Art Cell Detection in Bone Marrow Slide Images
In: Journal of Pathology Informatics 12 (1)
2021
Philipp Gräbel, Martina Crysandt, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Guided Representation Learning for the Classification of Hematopoietic Cells
In: ICCV Workshop on Computational Challenges in Digital Pathology (CDPath)
2021
Philipp Gräbel, Ina Laube, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Surrounding Cell Suppression for Unsupervised Representation Learning in Hematological Cell Classification
In: IEEE International Symposium on Biomedical Imaging (ISBI)
2021
Philipp Gräbel, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Reduction of stain variability in bone marrow microscopy images
In: Bildverarbeitung fuer die Medizin (BVM)
2021
Philipp Gräbel, Ina Laube, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Rotation invariance for unsupervised cell representation learning
In: Bildverarbeitung fuer die Medizin (BVM)
2020
Philipp Gräbel, Gregor Nickel, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Systematic Analysis and Automated Search of Hyper-parameters for Cell Classifier Training
In: IEEE International Symposium on Biomedical Imaging (ISBI)
2020
Philipp Gräbel, Özcan Özkan, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Circular Anchors for the Detection of Hematopoietic Cells using RetinaNet
In: IEEE International Symposium on Biomedical Imaging (ISBI)
2019
Philipp Gräbel, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Refinement of Weak Annotations for the Segmentation of Bone Marrow Leukocytes
In: 2nd MICCAI Workshop on Computational Pathology (COMPAY)
2018
Philipp Gräbel, Martina Crysandt, Reinhild Herwartz, Melanie Hoffmann, Barbara M. Klinkhammer, Peter Boor, Tim H. Brümmendorf, Dorit Merhof
Evaluating Out-of-the-box Methods for the Classification of Hematopoietic Cells in Images of Stained Bone Marrow
In: 1st MICCAI Workshop on Computational Pathology (COMPAY)