pathology analysis | Digital pathology and computational image analysi

Keyword	CPC	PCC	Volume	Score	Length of keyword
pathology analysis	1.63	0.8	4893	75	18
pathology	1.73	1	9363	57	9
analysis	1.66	0.8	1776	3	8

Keyword	CPC	PCC	Volume	Score
pathology analysis	1.77	0.9	5246	23
pathological analysis equipments	1.52	0.4	1114	23
melbourne pathology semen analysis	0.43	0.3	2850	90
brain pathology impact factor analysis	1.47	0.8	3757	51
online speech pathology data analysis	1.51	0.2	3601	30
request for surgical pathology analysis slip	0.1	0.9	7888	31

Search Results related to pathology analysis on Search Engine

Digital pathology and computational image analysis in ... - Nature
nature.com

https://www.nature.com/articles/s41581-020-0321-6

WEBAug 26, 2020 · Developments in digital pathology and computational image analysis have the potential to identify new disease mechanisms, improve disease classification and prognostication, and ultimately aid...

DA: 51 PA: 17 MOZ Rank: 3

A visual–language foundation model for pathology image analysis …
nature.com

https://www.nature.com/articles/s41591-023-02504-3

WEBAug 17, 2023 · Using extracted images and related labels from pathology-related tweets, a model is trained to associate tissue images and text and approaches state-of-the-art performance in clinically relevant...

DA: 63 PA: 100 MOZ Rank: 92

Artificial intelligence and computational pathology | Laboratory
nature.com

https://www.nature.com/articles/s41374-020-00514-0

WEBJan 16, 2021 · Digital pathology includes the process of digitizing histopathology, immunohistochemistry or cytology slides using whole-slide scanners as well as the interpretation, management, and analysis of ...

DA: 73 PA: 77 MOZ Rank: 70

Developing image analysis methods for digital pathology - PMC
nih.gov

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324951/

WEBMay 23, 2022 · This very brief overview aims to demonstrate the overlaps between image processing, machine‐learning, and deep‐learning approaches to digital pathology analysis. Ultimately, all are applied to the pixel values of the image. Convolution—scaling and summing neighbouring pixel values—plays a starring role in each case.

DA: 47 PA: 11 MOZ Rank: 66

Application of Artificial Intelligence in Pathology: Trends and
nih.gov

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9688959/

WEBNov 15, 2022 · A branch of pathology that involves computational analysis of a broad array of methods to analyze patient specimens for the study of disease. In this paper, we focus on the extraction of information from digitized pathology images in combination with their associated metadata, typically using AI methods such as deep learning.

DA: 4 PA: 96 MOZ Rank: 82

Digital Pathology and Artificial Intelligence Applications in Pathology
nih.gov

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098984/

WEBApr 29, 2022 · Pathological diagnosis requires a detailed review of all medical data and past pathological data of the patient, and digital pathology enables the integrated analysis of data-based medical data. One of the important advantages of digital pathology is that pathological AI-based models can be easily used during the diagnostic process and ...

DA: 73 PA: 42 MOZ Rank: 37

How to use AI in pathology - Schüffler - Wiley Online Library
wiley.com

https://onlinelibrary.wiley.com/doi/full/10.1002/gcc.23178

WEBMay 31, 2023 · AI plays an important role in pathology, both in clinical practice supporting pathologists in their daily work, and in research discovering novel biomarkers for improved patient care. Still, AI is in its starting phase, and many pathology labs still need to transition to a digital workflow to be able to enjoy the benefits of AI.

DA: 97 PA: 72 MOZ Rank: 95

Pathology Image Analysis Using Segmentation Deep Learning Algorithms
sciencedirect.com

https://www.sciencedirect.com/science/article/pii/S0002944018311210

WEBSep 1, 2019 · Accelerating clinical diagnosis from pathology images and automating image analysis efficiently and accurately remain significant challenges. Recently, deep learning algorithms have shown great promise in pathology image analysis, such as in tumor region identification, metastasis detection, and patient prognosis.

DA: 76 PA: 39 MOZ Rank: 3

Pathology Image Analysis Using Segmentation Deep Learning ... - PubMed
nih.gov

https://pubmed.ncbi.nlm.nih.gov/31199919/

WEBAccelerating clinical diagnosis from pathology images and automating image analysis efficiently and accurately remain significant challenges. Recently, deep learning algorithms have shown great promise in pathology image analysis, such as in tumor region identification, metastasis detection, and patient prognosis.

DA: 43 PA: 35 MOZ Rank: 25

[2401.02651] Benchmarking PathCLIP for Pathology Image Analysis …
arxiv.org

https://arxiv.org/abs/2401.02651

WEBJan 5, 2024 · The recent contrastive language-image pretraining (CLIP) model has shown remarkable proficiency in understanding natural images. Drawing inspiration from CLIP, PathCLIP is specifically designed for pathology image analysis, utilizing over 200,000 image and text pairs in training.

DA: 95 PA: 26 MOZ Rank: 53