Filters








6 Hits in 7.5 sec

PointNu-Net: Simultaneous Multi-tissue Histology Nuclei Segmentation and Classification in the Clinical Wild [article]

Kai Yao and Kaizhu Huang and Jie Sun and Amir Hussain and Curran Jude
2021 arXiv   pre-print
We address the detection and classification of each nuclei as a novel semantic keypoint estimation problem to determine the center point of each nuclei.  ...  Automatic nuclei segmentation and classification plays a vital role in digital pathology.  ...  heatmap regression and segments nuclei simultaneously via dynamic convolution.  ... 
arXiv:2111.01557v1 fatcat:ruwivk7uobcdzjxm2rbzk2rqde

Recent Advances of Deep Learning for Computational Histopathology: Principles and Applications

Yawen Wu, Michael Cheng, Shuo Huang, Zongxiang Pei, Yingli Zuo, Jianxin Liu, Kai Yang, Qi Zhu, Jie Zhang, Honghai Hong, Daoqiang Zhang, Kun Huang (+2 others)
2022 Cancers  
Followed by the discussion of color normalization, we review applications of the deep learning method for various H&E-stained image analysis tasks such as nuclei and tissue segmentation.  ...  With the remarkable success of digital histopathology, we have witnessed a rapid expansion of the use of computational methods for the analysis of digital pathology and biopsy image patches.  ...  [75] proposed a panoptic segmentation model which incorporates an auxiliary semantic segmentation branch with the instance branch to integrate global and local features for nuclei segmentation.  ... 
doi:10.3390/cancers14051199 pmid:35267505 pmcid:PMC8909166 fatcat:7tfcfh4z45goxbcgf23sncok5a

Marker-controlled watershed with deep edge emphasis and optimized H-minima transform for automatic segmentation of densely cultivated 3D cell nuclei

Tuomas Kaseva, Bahareh Omidali, Eero Hippeläinen, Teemu Mäkelä, Ulla Wilppu, Alexey Sofiev, Arto Merivaara, Marjo Yliperttula, Sauli Savolainen, Eero Salli
2022 BMC Bioinformatics  
In recent years, one popular method for automatic segmentation of nuclei has been deep learning enhanced marker-controlled watershed transform.  ...  We studied whether this method could be improved for the segmentation of densely cultivated 3D nuclei via developing multiple system configurations in which we studied the effect of edge emphasizing CNNs  ...  Acknowledgements The authors wish to thank the Finnish Computing Competence Infrastructure (FCCI) for supporting this project with computational and data storage resources.  ... 
doi:10.1186/s12859-022-04827-3 pmid:35864453 pmcid:PMC9306214 fatcat:vvmbln2srfenjphchechpsegwu

Deep Semantic Segmentation of Natural and Medical Images: A Review [article]

Saeid Asgari Taghanaki, Kumar Abhishek, Joseph Paul Cohen, Julien Cohen-Adad, Ghassan Hamarneh
2020 arXiv   pre-print
The semantic image segmentation task consists of classifying each pixel of an image into an instance, where each instance corresponds to a class.  ...  sequenced models, weakly supervised, and multi-task methods and provide a comprehensive review of the contributions in each of these groups.  ...  Therefore, a promising direction for semantic image segmentation is to develop weakly supervised segmentation models.  ... 
arXiv:1910.07655v3 fatcat:uxrrmb3jofcsvnkfkuhfwi62yq

Image analysis in digital pathology based on machine learning techniques & deep neural networks [article]

Πάρις-Παναγιώτης Αμερικάνος, Paris-Panagiotis Amerikanos, University Of Piraeus, Ηλίας Μαγκλογιάννης
2020
Nuclei Segmentation Nuclei Segmentation Epithelium Segmentation Tubule Segmentation Tubule Segmentation Table 8 : 8 Nuclei Segmentation resultsEpithelium Segmentation: Five folds of  ...  Detectron2 is a ground-up rewrite of Detectron (originating from Mask R-CNN-benchmark), is powered by PyTorch, trains faster, and includes features such as Panoptic Segmentation, Densepose, R-CNN, rotated  ...  To address this, for most similar tasks staining normalization is performed as a preprocessing step.  ... 
doi:10.26267/unipi_dione/362 fatcat:nzpgvumgirclnmcfdhnvnv4mnu

Proceedings of the 2022 Joint Workshop of the German Research Training Groups in Computer Science

Felix Freiling, Helmut Seidl, 2022 2022 Joint Workshop Of The German Research Training Groups In Computer Science June 12–June 15
2022
Because last year's event marked the 25th anniversary of the workshop series, it featured a live interview with Professor Otto Spaniol who had initiated the workshop series in 1996.  ...  Returning to Dagstuhl and hosting this meeting as an in-person-only event was a deliberate decision to revive interaction modes that many of the funded researchers had yet to experience: fostering personal  ...  For this, we use Convolutional Neural Networks (CNNs) to do panoptic segmentation on gigapixel 2D HE whole-slide images.  ... 
doi:10.25593/opus4-fau-19321 fatcat:ry4vd32xxbgldirrvymuaxxqwi