Contact us
|
Home
|
Login
| Users Online: 42
Feedback
Subscribe
Advertise
Search
Advanced Search
Month wise articles
Figures next to the month indicate the number of articles in that month
2022
March
[
1
]
January
[
10
]
2021
December
[
7
]
November
[
9
]
September
[
8
]
August
[
2
]
July
[
1
]
June
[
4
]
May
[
3
]
April
[
4
]
March
[
7
]
February
[
3
]
January
[
6
]
2020
December
[
2
]
November
[
5
]
October
[
3
]
September
[
2
]
August
[
8
]
July
[
4
]
June
[
2
]
May
[
1
]
April
[
3
]
March
[
3
]
February
[
6
]
January
[
1
]
2019
December
[
6
]
November
[
4
]
September
[
4
]
August
[
3
]
July
[
6
]
June
[
1
]
May
[
2
]
April
[
6
]
March
[
3
]
February
[
4
]
January
[
2
]
2018
December
[
10
]
November
[
4
]
October
[
3
]
September
[
4
]
August
[
1
]
July
[
3
]
June
[
5
]
May
[
4
]
April
[
10
]
March
[
2
]
February
[
4
]
2017
December
[
5
]
November
[
4
]
October
[
3
]
September
[
9
]
July
[
5
]
June
[
2
]
May
[
4
]
April
[
6
]
March
[
6
]
February
[
7
]
2016
December
[
7
]
November
[
5
]
October
[
3
]
September
[
7
]
August
[
1
]
July
[
7
]
May
[
8
]
April
[
7
]
March
[
4
]
February
[
2
]
January
[
5
]
2015
November
[
4
]
October
[
5
]
September
[
5
]
August
[
4
]
July
[
3
]
June
[
19
]
May
[
5
]
April
[
1
]
March
[
5
]
February
[
9
]
January
[
3
]
2014
November
[
2
]
October
[
5
]
September
[
4
]
August
[
6
]
July
[
8
]
June
[
1
]
May
[
3
]
March
[
8
]
February
[
3
]
January
[
4
]
2013
December
[
5
]
November
[
2
]
October
[
4
]
September
[
4
]
August
[
3
]
July
[
3
]
June
[
5
]
May
[
7
]
March
[
18
]
February
[
1
]
January
[
1
]
2012
December
[
6
]
November
[
1
]
October
[
4
]
September
[
4
]
August
[
7
]
July
[
2
]
June
[
1
]
May
[
2
]
April
[
7
]
March
[
6
]
February
[
7
]
January
[
13
]
2011
December
[
3
]
November
[
1
]
October
[
7
]
August
[
9
]
July
[
3
]
June
[
7
]
May
[
3
]
March
[
6
]
February
[
8
]
January
[
6
]
2010
December
[
4
]
November
[
1
]
October
[
6
]
September
[
1
]
August
[
6
]
July
[
6
]
May
[
5
]
» Articles published in the past year
To view other articles click corresponding year from the navigation links on the left side.
All
|
Abstracts
|
Book Review
|
Commentary
|
Editorial
|
Letters to Editor
|
Original Article
|
Original Articles
|
PV16 Abstracts
|
Research Article
|
Review Articles
|
Symposium
|
Technical Note
Export selected to
Endnote
Reference Manager
Procite
Medlars Format
RefWorks Format
BibTex Format
Show all abstracts
Show selected abstracts
Export selected to
Add to my list
Original Article:
Deep learning for classification of colorectal polyps on whole-slide images
Bruno Korbar, Andrea M Olofson, Allen P Miraflor, Catherine M Nicka, Matthew A Suriawinata, Lorenzo Torresani, Arief A Suriawinata, Saeed Hassanpour
J Pathol Inform
2017, 8:30 (25 July 2017)
DOI
:10.4103/jpi.jpi_34_17
PMID
:28828201
Context:
Histopathological characterization of colorectal polyps is critical for determining the risk of colorectal cancer and future rates of surveillance for patients. However, this characterization is a challenging task and suffers from significant inter- and intra-observer variability.
Aims:
We built an automatic image analysis method that can accurately classify different types of colorectal polyps on whole-slide images to help pathologists with this characterization and diagnosis.
Setting and Design:
Our method is based on deep-learning techniques, which rely on numerous levels of abstraction for data representation and have shown state-of-the-art results for various image analysis tasks.
Subjects and Methods:
Our method covers five common types of polyps (i.e., hyperplastic, sessile serrated, traditional serrated, tubular, and tubulovillous/villous) that are included in the US Multisociety Task Force guidelines for colorectal cancer risk assessment and surveillance. We developed multiple deep-learning approaches by leveraging a dataset of 2074 crop images, which were annotated by multiple domain expert pathologists as reference standards.
Statistical Analysis:
We evaluated our method on an independent test set of 239 whole-slide images and measured standard machine-learning evaluation metrics of accuracy, precision, recall, and F1 score and their 95% confidence intervals.
Results:
Our evaluation shows that our method with residual network architecture achieves the best performance for classification of colorectal polyps on whole-slide images (overall accuracy: 93.0%, 95% confidence interval: 89.0%–95.9%).
Conclusions:
Our method can reduce the cognitive burden on pathologists and improve their efficacy in histopathological characterization of colorectal polyps and in subsequent risk assessment and follow-up recommendations.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (69) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Original Article:
PathEdEx – Uncovering high-explanatory visual diagnostics heuristics using digital pathology and multiscale gaze data
Dmitriy Shin, Mikhail Kovalenko, Ilker Ersoy, Yu Li, Donald Doll, Chi-Ren Shyu, Richard Hammer
J Pathol Inform
2017, 8:29 (25 July 2017)
DOI
:10.4103/jpi.jpi_29_17
PMID
:28828200
Background:
Visual heuristics of pathology diagnosis is a largely unexplored area where reported studies only provided a qualitative insight into the subject. Uncovering and quantifying pathology visual and nonvisual diagnostic patterns have great potential to improve clinical outcomes and avoid diagnostic pitfalls.
Methods:
Here, we present PathEdEx, an informatics computational framework that incorporates whole-slide digital pathology imaging with multiscale gaze-tracking technology to create web-based interactive pathology educational atlases and to datamine visual and nonvisual diagnostic heuristics.
Results:
We demonstrate the capabilities of PathEdEx for mining visual and nonvisual diagnostic heuristics using the first PathEdEx volume of a hematopathology atlas. We conducted a quantitative study on the time dynamics of zooming and panning operations utilized by experts and novices to come to the correct diagnosis. We then performed association rule mining to determine sets of diagnostic factors that consistently result in a correct diagnosis, and studied differences in diagnostic strategies across different levels of pathology expertise using Markov chain (MC) modeling and MC Monte Carlo simulations. To perform these studies, we translated raw gaze points to high-explanatory semantic labels that represent pathology diagnostic clues. Therefore, the outcome of these studies is readily transformed into narrative descriptors for direct use in pathology education and practice.
Conclusion:
PathEdEx framework can be used to capture best practices of pathology visual and nonvisual diagnostic heuristics that can be passed over to the next generation of pathologists and have potential to streamline implementation of precision diagnostics in precision medicine settings.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (2) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Technical Note:
Implementation of automated calculation of free and bioavailable testosterone in Epic Beaker laboratory information system
Michael C Chung, Saurabh Gombar, Run Zhang Shi
J Pathol Inform
2017, 8:28 (25 July 2017)
DOI
:10.4103/jpi.jpi_28_17
PMID
:28828199
Background:
Automated calculations by laboratory information system (LIS) are efficient and accurate ways of providing calculated laboratory test results. Due to the lack of established advanced mathematical functions and equation logic in LIS software, calculations beyond simple arithmetic functions require a tedious workaround. Free and bioavailable testosterone (BT) calculations require a quadratic solver currently unavailable as ready to use the function on most commercial LIS platforms. We aimed to develop a module within the Epic Beaker LIS to enable automatic quadratic equation solving capability and real-time reporting of calculated free and BT values.
Materials and Methods:
We developed and implemented an advanced calculation module from the ground up using existing basic calculation programming functions in the Epic Beaker LIS. A set of calculation variables were created, and mathematical logic and functions were used to link the variables and perform the actual quadratic equation based calculations. Calculations were performed in real-time during result entry events, and calculated results populated the result components in LIS automatically.
Results:
Free and BT were calculated using instrument measured results of total testosterone, sex hormone binding globulin, and/or serum albumin, by applying equations widely adopted in laboratory medicine for endocrine diseases and disorders. Calculated results in Epic Beaker LIS were then compared and confirmed by manual calculations using Microsoft Excel spreadsheets and scientific calculators to have no discrepancies.
Conclusions:
Automated calculations of free and BT were successfully implemented and validated, the first of such implementation for the Epic Beaker LIS platform, eliminating the need of offline manual calculations, potential transcription error, and with improved turnaround time. It may serve as a model to build similarly complex equations when the clinical need arises.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (6) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Original Article:
Teaching digital pathology: The international school of digital pathology and proposed syllabus
Vincenzo Della Mea, Antonino Carbone, Carla Di Loreto, Gloria Bueno, Paolo De Paoli, Marcial García-Rojo, David de Mena, Annunziata Gloghini, Mohammad Ilyas, Arvydas Laurinavicius, Allan Rasmusson, Massimo Milione, Riccardo Dolcetti, Marco Pagani, Andrea Stoppini, Sandro Sulfaro, Michelangelo Bartolo, Emanuela Mazzon, H Peter Soyer, Liron Pantanowitz
J Pathol Inform
2017, 8:27 (25 July 2017)
DOI
:10.4103/jpi.jpi_17_17
PMID
:28828198
Digital pathology is an interdisciplinary field where competency in pathology, laboratory techniques, informatics, computer science, information systems, engineering, and even biology converge. This implies that teaching students about digital pathology requires coverage, expertise, and hands-on experience in all these disciplines. With this in mind, a syllabus was developed for a digital pathology summer school aimed at professionals in the aforementioned fields, as well as trainees and doctoral students. The aim of this communication is to share the context, rationale, and syllabus for this school of digital pathology.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (2) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Abstracts:
Pathology Informatics Summit 2017
J Pathol Inform
2017, 8:26 (14 July 2017)
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Sword Plugin for Repository]
Beta
Sitemap
|
What's New
Feedback
|
Copyright and Disclaimer
|
Privacy Notice
© Journal of Pathology Informatics | Published by Wolters Kluwer -
Medknow
Online since 10
th
March, 2010