Melanoma Segmentation and Classification Employing Imaging and Graph Encodings
Rivera Monroy L, Eberhardt M, Ostalecki C, Baur A, Vera J, Maier A (2022)
Publication Type: Conference contribution
Publication year: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 144-145
Conference Proceedings Title: Proceedings - 2022 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2022
Event location: Washington, DC
ISBN: 9781450394765
Abstract
Histopathology imaging is crucial for the diagnosis and the decision on treating associated tissue diseases. For this reason, Computer-assisted approaches have gained popularity and shown promise in tasks such as segmentation and classification. However, collecting a significant amount of data and high-quality annotations remains a challenge. This work describes a pipeline for toponomy profiling on the population of cells that combines melanoma multidimensional fluorescent imaging, a supervised segmentation of the region of interest, and graph unsupervised embedded representation.The Multi-Epitope-Ligand Cartography (MELC) provides a range of data shown to be optimal for solving supervised and unsuper-vised tasks. This imaging technique and the methodology, such as the one presented here, are promising for further improvement in the study of diagnostic techniques and therapies for skin diseases, such as melanoma.
Authors with CRIS profile
Luis Rivera Monroy
Department of Dermatology
Martin Eberhardt
Department of Dermatology
Christian Ostalecki
Department of Psychiatry and Psychotherapy
Andreas Baur
Department of Dermatology
Julio Vera González
Professur für Tumorimmunologie (Schwerpunkt Systembiologie)
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
How to cite
APA:
Rivera Monroy, L., Eberhardt, M., Ostalecki, C., Baur, A., Vera, J., & Maier, A. (2022). Melanoma Segmentation and Classification Employing Imaging and Graph Encodings. In Proceedings - 2022 IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2022 (pp. 144-145). Washington, DC, US: Institute of Electrical and Electronics Engineers Inc..
MLA:
Rivera Monroy, Luis, et al. "Melanoma Segmentation and Classification Employing Imaging and Graph Encodings." Proceedings of the 7th IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies, CHASE 2022, Washington, DC Institute of Electrical and Electronics Engineers Inc., 2022. 144-145.
BibTeX: Download