Song, Sifan 
ORCID: 0000-0002-7940-650X, Wang, Jinfeng, Cheng, Fengrui, Cao, Qirui, Zuo, Yihan, Lei, Yongteng, Yang, Ruomai, Yang, Chunxiao, Coenen, Frans ORCID: 0000-0003-1026-6649, Meng, Jia ORCID: 0000-0003-3455-205X et al (show 2 more authors)
(2023)
A Robust Framework of Chromosome Straightening With Vit-Patch Gan.
In: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023-4-18 - 2023-4-21.
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Abstract
Chromosomes carry the genetic information of humans. They exhibit non-rigid and non-articulated nature with varying degrees of curvature. Chromosome straightening is an important step for subsequent karyotype construction, pathological diagnosis and cytogenetic map development. However, robust chromosome straightening remains challenging, due to the unavailability of training images, distorted chromosome details and shapes after straightening, as well as poor generalization capability. In this paper, we propose a novel architecture, ViT-Patch GAN, consisting of a self-learned motion transformation generator and a Vision Transformer-based patch (ViT-Patch) discriminator. The generator learns the motion representation of chromosomes for straightening. With the help of the ViT-Patch discriminator, the straightened chromosomes retain more shape and banding pattern details. The experimental results show that the proposed method achieves better performance on Fréchet Inception Distance (FID), Learned Perceptual Image Patch Similarity (LPIPS) and downstream chromosome classification accuracy, and shows excellent generalization capability on a large dataset.
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 01 Mar 2023 09:41 |
| Last Modified: | 14 Mar 2024 21:44 |
| DOI: | 10.1109/isbi53787.2023.10230388 |
| Related URLs: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3168644 |
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