تقرير
Employing Graph Representations for Cell-level Characterization of Melanoma MELC Samples
| العنوان: | Employing Graph Representations for Cell-level Characterization of Melanoma MELC Samples |
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| المؤلفون: | Monroy, Luis Carlos Rivera, Rist, Leonhard, Eberhardt, Martin, Ostalecki, Christian, Baur, Andreas, Vera, Julio, Breininger, Katharina, Maier, Andreas |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Computational Engineering, Finance, and Science |
| الوصف: | Histopathology imaging is crucial for the diagnosis and treatment of skin diseases. For this reason, computer-assisted approaches have gained popularity and shown promising results in tasks such as segmentation and classification of skin disorders. However, collecting essential data and sufficiently high-quality annotations is a challenge. This work describes a pipeline that uses suspected melanoma samples that have been characterized using Multi-Epitope-Ligand Cartography (MELC). This cellular-level tissue characterisation is then represented as a graph and used to train a graph neural network. This imaging technology, combined with the methodology proposed in this work, achieves a classification accuracy of 87%, outperforming existing approaches by 10%. Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2211.05884 |
| رقم الأكسشن: | edsarx.2211.05884 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |