[HTML][HTML] Tertiary lymphoid structures (TLS) identification and density assessment on H&E-stained digital slides of lung cancer
P Barmpoutis, M Di Capite, H Kayhanian… - Plos one, 2021 - journals.plos.org
Tertiary lymphoid structures (TLS) are ectopic aggregates of lymphoid cells in inflamed,
infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete …
infected, or tumoral tissues that are easily recognized on an H&E histology slide as discrete …
An Atrous Convolved Hybrid Seg-Net Model with residual and attention mechanism for gland detection and segmentation in histopathological images
Purpose A clinically compatible computerized segmentation model is presented here that
aspires to supply clinical gland informative details by seizing every small and intricate …
aspires to supply clinical gland informative details by seizing every small and intricate …
MTU: A multi-tasking U-net with hybrid convolutional learning and attention modules for cancer classification and gland Segmentation in Colon Histopathological …
A clinically comparable multi-tasking computerized deep U-Net-based model is
demonstrated in this paper. It intends to offer clinical gland morphometric information and …
demonstrated in this paper. It intends to offer clinical gland morphometric information and …
[HTML][HTML] Attention-Guided deep atrous-residual U-Net architecture for automated gland segmentation in colon histopathology images
In digital pathology, gland segmentation plays a dominant part in the diagnosis and
quantification of colon cancer. Thus, this paper presents a clinically relevant deep learning …
quantification of colon cancer. Thus, this paper presents a clinically relevant deep learning …
[HTML][HTML] A hybrid U-Net model with attention and advanced convolutional learning modules for simultaneous gland segmentation and cancer grade prediction in …
In this proposed research work, a computerized Hybrid U-Net model for supplying colon
glandular morphometric and cancer grade information is demonstrated. The solution is put …
glandular morphometric and cancer grade information is demonstrated. The solution is put …
Dense Dilated Multi-Scale Supervised Attention-Guided Network for histopathology image segmentation
Over the last couple of decades, the introduction and proliferation of whole-slide scanners
led to increasing interest in the research of digital pathology. Although manual analysis of …
led to increasing interest in the research of digital pathology. Although manual analysis of …
An accelerated pipeline for multi-label renal pathology image segmentation at the whole slide image level
Deep-learning techniques have been used widely to alleviate the labour-intensive and time-
consuming manual annotation required for pixel-level tissue characterization. Our previous …
consuming manual annotation required for pixel-level tissue characterization. Our previous …
Preprocessing techniques for colon histopathology images
The glandular morphology analysis done within the colon histopathological images is an
imperative step for grade determination of colon cancer. But the manual segmentation is …
imperative step for grade determination of colon cancer. But the manual segmentation is …
Effect analysis of contrast enhancement techniques on cancer classification in colon histopathology images using machine learning
The glandular morphology analysis done within the colon histopathological images is a
crucial step required for grade determination of colon cancer. But the manual segmentation …
crucial step required for grade determination of colon cancer. But the manual segmentation …
Combining deep learning with handcrafted features for cell nuclei segmentation
H Narotamo, JM Sanches… - 2020 42nd annual …, 2020 - ieeexplore.ieee.org
Segmentation of cell nuclei in fluorescence microscopy images provides valuable
information about the shape and size of the nuclei, its chromatin texture and DNA content. It …
information about the shape and size of the nuclei, its chromatin texture and DNA content. It …