Contact us
|
Home
|
Login
| Users Online: 1641
Feedback
Subscribe
Advertise
Search
Advanced Search
Month wise articles
Figures next to the month indicate the number of articles in that month
2019
February
[
3
]
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
]
1900
January
[
1
]
» 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
|
Commentaries
|
Commentary
|
Editorial
|
Letters to Editor
|
Original Article
|
Original Articles
|
Original Research
|
Original Research Article
|
Research Article
|
Research Articles
|
Review Articles
|
Symposium
|
Technical Note
|
Technical Note: Software
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:
A quantitative approach to evaluate image quality of whole slide imaging scanners
Prarthana Shrestha, R Kneepkens, J Vrijnsen, D Vossen, E Abels, B Hulsken
J Pathol Inform
2016, 7:56 (30 December 2016)
DOI
:10.4103/2153-3539.197205
PMID
:28197359
Context:
The quality of images produced by whole slide imaging (WSI) scanners has a direct influence on the readers' performance and reliability of the clinical diagnosis. Therefore, WSI scanners should produce not only high quality but also consistent quality images.
Aim:
We aim to evaluate reproducibility of WSI scanners based on the quality of images produced over time and among multiple scanners. The evaluation is independent of content or context of test specimen.
Methods:
The ultimate judge of image quality is a pathologist, however, subjective evaluations are heavily influenced by the complexity of a case and subtle variations introduced by a scanner can be easily overlooked. Therefore, we employed a quantitative image quality assessment method based on clinically relevant parameters, such as sharpness and brightness, acquired in a survey of pathologists. The acceptable level of quality per parameter was determined in a subjective study. The evaluation of scanner reproducibility was conducted with Philips Ultra-Fast Scanners. A set of 36 HercepTest™ slides were used in three sub-studies addressing variations due to systems and time, producing 8640 test images for evaluation.
Results:
The results showed that the majority of images in all the sub-studies are within the acceptable quality level; however, some scanners produce higher quality images more often than others. The results are independent of case types, and they match our perception of quality.
Conclusion:
The quantitative image quality assessment method was successfully applied in the HercepTest™ slides to evaluate WSI scanner reproducibility. The proposed method is generic and applicable to any other types of slide stains and scanners.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[PubMed]
[Sword Plugin for Repository]
Beta
Technical Note: Software:
Generating unique IDs from patient identification data using security models
Emad A Mohammed, Jonathan C Slack, Christopher T Naugler
J Pathol Inform
2016, 7:55 (30 December 2016)
DOI
:10.4103/2153-3539.197203
PMID
:28163977
Background:
The use of electronic health records (EHRs) has continued to increase within healthcare systems in the developed and developing nations. EHRs allow for increased patient safety, grant patients easier access to their medical records, and offer a wealth of data to researchers. However, various bioethical, financial, logistical, and information security considerations must be addressed while transitioning to an EHR system. The need to encrypt private patient information for data sharing is one of the foremost challenges faced by health information technology.
Method:
We describe the usage of the message digest-5 (MD5) and secure hashing algorithm (SHA) as methods for encrypting electronic medical data. In particular, we present an application of the MD5 and SHA-1 algorithms in encrypting a composite message from private patient information.
Results:
The results show that the composite message can be used to create a unique one-way encrypted ID per patient record that can be used for data sharing.
Conclusion:
The described software tool can be used to share patient EMRs between practitioners without revealing patients identifiable data.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[PubMed]
[Sword Plugin for Repository]
Beta
Original Article:
Reporting Gleason grade/score in synoptic reports of radical prostatectomies
Andrew A Renshaw, Mercy Mena-Allauca, Edwin W Gould
J Pathol Inform
2016, 7:54 (30 December 2016)
DOI
:10.4103/2153-3539.197201
PMID
:28163976
Context:
The format of a synoptic report can significantly affect the accuracy, speed, and preference with which a reader can retrieve information.
Objective:
The objective of this study is to compare different formats of Gleason grading/score in synoptic reports of radical prostatectomies.
Methods:
The performance of 16 nonpathologists (cancer registrars, MDs, medical non-MDs, and nonmedical) at identifying specific information in various formatted synoptic reports using a computerized quiz that measured both accuracy and speed.
Results:
Compared to the standard format (primary, secondary, tertiary grades, and total score on separate lines), omitting tertiary grade when "Not applicable" reduced accuracy (72 vs. 97%,
P
< 0.001) and increased time to retrieve information 63% (
P
< 0.001). No user preferred to have tertiary grade omitted. Both the biopsy format (primary + secondary = total score, tertiary on a separate line) and the single line format (primary + secondary + (tertiary) -> total score) were associated with increased speed of data extraction (18 and 24%, respectively,
P
< 0.001). The single line format was more accurate (100% vs. 97%,
P
= 0.02). No user preferred the biopsy format, and only 7/16 users preferred the single line format.
Conclusions
: Different report formats for Gleason grading significantly affect users speed, accuracy, and preference; users do not always prefer either speed or accuracy.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (2) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Technical Note:
Use of application containers and workflows for genomic data analysis
Wade L Schulz, Thomas Durant, Alexa J Siddon, Richard Torres
J Pathol Inform
2016, 7:53 (30 December 2016)
DOI
:10.4103/2153-3539.197197
PMID
:28163975
Background:
The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments.
Methods:
Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing.
Results:
While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data.
Conclusions:
With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Citations (6) ]
[PubMed]
[Sword Plugin for Repository]
Beta
Book Review:
Review of "Digital Pathology Resource Guide, Version 6.0 Issue No. 1, 2016" by College of American Pathologists Digital Pathology Committee
Julie Diane Gibbs, Marilyn M Bui
J Pathol Inform
2016, 7:52 (30 December 2016)
DOI
:10.4103/2153-3539.197196
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[Sword Plugin for Repository]
Beta
Original Research:
Enhancements in localized classification for uterine cervical cancer digital histology image assessment
Peng Guo, Haidar Almubarak, Koyel Banerjee, R Joe Stanley, Rodney Long, Sameer Antani, George Thoma, Rosemary Zuna, Shelliane R Frazier, Randy H Moss, William V Stoecker
J Pathol Inform
2016, 7:51 (30 December 2016)
DOI
:10.4103/2153-3539.197193
PMID
:28163974
Background:
In previous research, we introduced an automated, localized, fusion-based approach for classifying uterine cervix squamous epithelium into Normal, CIN1, CIN2, and CIN3 grades of cervical intraepithelial neoplasia (CIN) based on digitized histology image analysis. As part of the CIN assessment process, acellular and atypical cell concentration features were computed from vertical segment partitions of the epithelium region to quantize the relative distribution of nuclei.
Methods:
Feature data was extracted from 610 individual segments from 61 images for epithelium classification into categories of Normal, CIN1, CIN2, and CIN3. The classification results were compared against CIN labels obtained from two pathologists who visually assessed abnormality in the digitized histology images. In this study, individual vertical segment CIN classification accuracy improvement is reported using the logistic regression classifier for an expanded data set of 118 histology images.
Results:
We analyzed the effects on classification using the same pathologist labels for training and testing versus using one pathologist labels for training and the other for testing. Based on a leave-one-out approach for classifier training and testing, exact grade CIN accuracies of 81.29% and 88.98% were achieved for individual vertical segment and epithelium whole-image classification, respectively.
Conclusions:
The Logistic and Random Tree classifiers outperformed the benchmark SVM and LDA classifiers from previous research. The Logistic Regression classifier yielded an improvement of 10.17% in CIN Exact grade classification results based on CIN labels for training-testing for the individual vertical segments and the whole image from the same single expert over the baseline approach using the reduced features. Overall, the CIN classification rates tended to be higher using the training-testing labels for the same expert than for training labels from one expert and testing labels from the other expert. The Exact class fusion- based CIN discrimination results obtained in this study are similar to the Exact class expert agreement rate.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[PubMed]
[Sword Plugin for Repository]
Beta
Original Article:
How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling
Agnieszka Onisko, Marek J Druzdzel, R Marshall Austin
J Pathol Inform
2016, 7:50 (30 December 2016)
DOI
:10.4103/2153-3539.197191
PMID
:28163973
Background:
Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data.
Aim:
The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data.
Materials
and
Methods:
This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years.
Results:
The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation.
Conclusion
: Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.
[ABSTRACT]
[HTML Full text]
[PDF]
[Mobile Full text]
[EPub]
[PubMed]
[Sword Plugin for Repository]
Beta
Sitemap
|
What's New
|
Feedback
|
Disclaimer
|
© Journal of Pathology Informatics | Published by Wolters Kluwer -
Medknow
Online since 10
th
March, 2010