![](images/graphics/blank.gif)
Nuclei segmentation
-
In the tumor microenvironment (TME), the dynamic interaction between tumor cells and immune cells plays a critical role in predicting the prognosis of colorectal cancer. This study introduces a novel approach based on artificial intelligence (AI) and immunohistochemistry (IHC)-stained whole-slide images (WSIs) of colorectal cancer (CRC) patients to quantitatively assess the spatial associations between tumor cells and immune cells.
10p
vioracle
29-09-2023
6
4
Download
-
This paper proposes an approach for segmentation of nuclei images based on deep learning. In particular, the recent TransUnet inspired from transformers’ strong ability in modeling long-range context, is employed and adapted for the nuclei segmentation.
5p
vigeneralmotors
13-07-2022
11
6
Download
-
For the analysis of spatio-temporal dynamics, various automated processing methods have been developed for nuclei segmentation. These methods tend to be complex for segmentation of images with crowded nuclei, preventing the simple reapplication of the methods to other problems.
11p
viwyoming2711
16-12-2020
7
0
Download
-
Analysis of cellular processes with microscopic bright field defocused imaging has the advantage of low phototoxicity and minimal sample preparation. However bright field images lack the contrast and nuclei reporting available with florescent approaches and therefore present a challenge to methods that segment and track the live cells.
10p
vikentucky2711
26-11-2020
10
0
Download
-
The protein ki67 (pki67) is a marker of tumor aggressiveness, and its expression has been proven to be useful in the prognostic and predictive evaluation of several types of tumors. To numerically quantify the pki67 presence in cancerous tissue areas, pathologists generally analyze histochemical images to count the number of tumor nuclei marked for pki67.
14p
vicolorado2711
23-10-2020
12
1
Download
-
Cell nuclei segmentation is a fundamental task in microscopy image analysis, based on which multiple biological related analysis can be performed. Although deep learning (DL) based techniques have achieved state-of-the-art performances in image segmentation tasks, these methods are usually complex and require support of powerful computing resources.
12p
vicolorado2711
23-10-2020
42
1
Download
CHỦ ĐỀ BẠN MUỐN TÌM
![](images/graphics/blank.gif)