Multi‐atlas thalamic nuclei segmentation on standard T1‐weighed MRI with application to normal aging
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DOI: 10.1002/hbm.26088
Abstract: Specific thalamic nuclei are implicated in healthy aging and age‐related neurodegenerative diseases. However, few methods are available for robust automated segmentation of thalamic nuclei. The threefold aims of this study were to validate the use… read more here.
Keywords: thalamic nuclei; nuclei segmentation; age; standard ... See more keywords
Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11873-1
Abstract: To improve the process of diagnosis and treatment of cancer disease, automatic segmentation of haematoxylin and eosin (H & E) stained cell nuclei from histopathology images is the first step in digital pathology. The proposed… read more here.
Keywords: histopathology; nuclei segmentation; segmentation; encoder decoder ... See more keywords
Integrating deep convolutional neural networks with marker-controlled watershed for overlapping nuclei segmentation in histopathology images
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.09.083
Abstract: Abstract Nuclei segmentation in histopathology images plays a crucial role in the morphological quantitative analysis of tissue structure and has become a hot research topic. Though numerous efforts have been tried in this research area,… read more here.
Keywords: segmentation; histopathology; controlled watershed; nuclei segmentation ... See more keywords
A Weakly Supervised Method With Colorization for Nuclei Segmentation Using Point Annotations
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Instrumentation and Measurement"
DOI: 10.1109/tim.2023.3265124
Abstract: Nuclei segmentation is an essential step in the automatic analysis of histopathology images. This segmentation task requires much work to manually generate accurate pixel-level annotations for fully supervised training. To overcome such expensive and hard-to-get… read more here.
Keywords: nuclei segmentation; weakly supervised; task; point annotations ... See more keywords
Breast cancer histopathological images recognition based on two-stage nuclei segmentation strategy
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DOI: 10.1371/journal.pone.0266973
Abstract: Pathological examination is the gold standard for breast cancer diagnosis. The recognition of histopathological images of breast cancer has attracted a lot of attention in the field of medical image processing. In this paper, on… read more here.
Keywords: nuclei segmentation; breast cancer; segmentation; histopathological images ... See more keywords
Nuclei segmentation of HE stained histopathological images based on feature global delivery connection network
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DOI: 10.1371/journal.pone.0273682
Abstract: The analysis of pathological images, such as cell counting and nuclear morphological measurement, is an essential part in clinical histopathology researches. Due to the diversity of uncertain cell boundaries after staining, automated nuclei segmentation of… read more here.
Keywords: nuclei segmentation; delivery connection; global delivery; segmentation ... See more keywords
Analyzing Cell-Scaffold Interaction through Unsupervised 3D Nuclei Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "International Journal of Bioprinting"
DOI: 10.18063/ijb.v8i1.495
Abstract: Fibrous scaffolds have been extensively used in three-dimensional (3D) cell culture systems to establish in vitro models in cell biology, tissue engineering, and drug screening. It is a common practice to characterize cell behaviors on… read more here.
Keywords: scaffold interaction; segmentation; nuclei segmentation; cell scaffold ... See more keywords
An Empirical Evaluation of Nuclei Segmentation from H&E Images in a Real Application Scenario
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DOI: 10.3390/app10227982
Abstract: Cell nuclei segmentation is a challenging task, especially in real applications, when the target images significantly differ between them. This task is also challenging for methods based on convolutional neural networks (CNNs), which have recently… read more here.
Keywords: cell nuclei; empirical evaluation; scenario; segmentation ... See more keywords
MIU-Net: MIX-Attention and Inception U-Net for Histopathology Image Nuclei Segmentation
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DOI: 10.3390/app13084842
Abstract: In the medical field, hematoxylin and eosin (H&E)-stained histopathology images of cell nuclei analysis represent an important measure for cancer diagnosis. The most valuable aspect of the nuclei analysis is the segmentation of the different… read more here.
Keywords: inception; nuclei segmentation; segmentation; attention ... See more keywords
GSN-HVNET: A Lightweight, Multi-Task Deep Learning Framework for Nuclei Segmentation and Classification
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DOI: 10.3390/bioengineering10030393
Abstract: Nuclei segmentation and classification are two basic and essential tasks in computer-aided diagnosis of digital pathology images, and those deep-learning-based methods have achieved significant success. Unfortunately, most of the existing studies accomplish the two tasks… read more here.
Keywords: segmentation classification; nuclei segmentation; classification; segmentation ... See more keywords