AFINITI: attention-aware feature integration for nuclei instance segmentation and type identification
Author:
Funder
Islamic World Educational, Scientific and Cultural. Organization
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00521-024-10114-4.pdf
Reference38 articles.
1. Nasir ES, Parvaiz A, Fraz MM (2023) Nuclei and glands instance segmentation in histology images: a narrative review. Artif Intell Rev 56:7909–7964. https://doi.org/10.1007/s10462-022-10372-5
2. Ahmad I, Xia Y, Cui H, Islam ZU (2023) Dan-nucnet: a dual attention based framework for nuclei segmentation. Expert Syst Appl 213:118945
3. Priego-Torres BM, Sanchez-Morillo D, Fernandez-Granero MA, Garcia-Rojo M (2020) Automatic segmentation of whole-slide h &e stained breast histopathology images using a deep convolutional neural network architecture. Expert Syst Appl 151:113387. https://doi.org/10.1016/j.eswa.2020.113387
4. Rashid SN, Fraz MM (2023) Nuclei probability and centroid map network for nuclei instance segmentation in histology images. Neural Comput Appl 35(21):15447–15460. https://doi.org/10.1007/s00521-023-08503-2
5. Graham S, Vu QD, Raza SEA, Azam A, Tsang YW, Kwak JT, Rajpoot N (2019) Hover-net: simultaneous segmentation and classification of nuclei in multi-tissue histology images. Med Image Anal 58:101563. https://doi.org/10.1016/j.media.2019.101563
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