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Month wise articles
Figures next to the month indicate the number of articles in that month
2021
April
[
4
]
March
[
7
]
February
[
3
]
January
[
6
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2020
December
[
2
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November
[
5
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October
[
3
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September
[
2
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August
[
8
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July
[
4
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June
[
2
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May
[
1
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April
[
3
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March
[
3
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February
[
6
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January
[
1
]
2019
December
[
6
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November
[
4
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September
[
4
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August
[
3
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July
[
6
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June
[
1
]
May
[
2
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April
[
6
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March
[
3
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February
[
4
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January
[
2
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2018
December
[
10
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November
[
4
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October
[
3
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September
[
4
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August
[
1
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July
[
3
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June
[
5
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May
[
4
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April
[
10
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March
[
2
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February
[
4
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2017
December
[
5
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November
[
4
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October
[
3
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September
[
9
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July
[
5
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June
[
2
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May
[
4
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April
[
6
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March
[
6
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February
[
7
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2016
December
[
7
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November
[
5
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October
[
3
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September
[
7
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August
[
1
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July
[
7
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May
[
8
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April
[
7
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March
[
4
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February
[
2
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January
[
5
]
2015
November
[
4
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October
[
5
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September
[
5
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August
[
4
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July
[
3
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June
[
19
]
May
[
5
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April
[
1
]
March
[
5
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February
[
9
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January
[
3
]
2014
November
[
2
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October
[
5
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September
[
4
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August
[
6
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July
[
8
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June
[
1
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May
[
3
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March
[
8
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February
[
3
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January
[
4
]
2013
December
[
5
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November
[
2
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October
[
4
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September
[
4
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August
[
3
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July
[
3
]
June
[
5
]
May
[
7
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March
[
18
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February
[
1
]
January
[
1
]
2012
December
[
6
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November
[
1
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October
[
4
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September
[
4
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August
[
7
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July
[
2
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June
[
1
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May
[
2
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April
[
7
]
March
[
6
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February
[
7
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January
[
13
]
2011
December
[
3
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November
[
1
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October
[
7
]
August
[
9
]
July
[
3
]
June
[
7
]
May
[
3
]
March
[
6
]
February
[
8
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January
[
6
]
2010
December
[
4
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November
[
1
]
October
[
6
]
September
[
1
]
August
[
6
]
July
[
6
]
May
[
5
]
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Editorial:
An industry perspective: An update on the adoption of whole slide imaging
Michael C Montalto
J Pathol Inform
2016, 7:18 (11 April 2016)
DOI
:10.4103/2153-3539.180014
PMID
:27141323
This manuscript is an adaptation of the closing keynote presentation of the Digital Pathology Association Pathology Visions Conference 2015 in Boston, MA, USA. In this presentation, analogies are drawn between the adoption of whole slide imaging (WSI) and other mainstream digital technologies, including digital music and books. In doing so, it is revealed that the adoption of seemingly similar digital technologies does not follow the same adoption profiles and that understanding the unique aspects of value for each customer segment is critical. Finally, a call to action is given to academia and industry to study the value that WSI brings to the global healthcare community.
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Research Article:
Empirical comparison of color normalization methods for epithelial-stromal classification in H and E images
Amit Sethi, Lingdao Sha, Abhishek Ramnath Vahadane, Ryan J Deaton, Neeraj Kumar, Virgilia Macias, Peter H Gann
J Pathol Inform
2016, 7:17 (11 April 2016)
DOI
:10.4103/2153-3539.179984
PMID
:27141322
Context:
Color normalization techniques for histology have not been empirically tested for their utility for computational pathology pipelines.
Aims:
We compared two contemporary techniques for achieving a common intermediate goal - epithelial-stromal classification.
Settings and Design:
Expert-annotated regions of epithelium and stroma were treated as ground truth for comparing classifiers on original and color-normalized images.
Materials and Methods:
Epithelial and stromal regions were annotated on thirty diverse-appearing H and E stained prostate cancer tissue microarray cores. Corresponding sets of thirty images each were generated using the two color normalization techniques. Color metrics were compared for original and color-normalized images. Separate epithelial-stromal classifiers were trained and compared on test images. Main analyses were conducted using a multiresolution segmentation (MRS) approach; comparative analyses using two other classification approaches (convolutional neural network [CNN],
Wndchrm
) were also performed.
Statistical Analysis:
For the main MRS method, which relied on classification of super-pixels, the number of variables used was reduced using backward elimination without compromising accuracy, and test - area under the curves (AUCs) were compared for original and normalized images. For CNN and
Wndchrm
, pixel classification test-AUCs were compared.
Results:
Khan method reduced color saturation while Vahadane reduced hue variance. Super-pixel-level test-AUC for MRS was 0.010-0.025 (95% confidence interval limits ± 0.004) higher for the two normalized image sets compared to the original in the 10-80 variable range. Improvement in pixel classification accuracy was also observed for CNN and
Wndchrm
for color-normalized images.
Conclusions:
Color normalization can give a small incremental benefit when a super-pixel-based classification method is used with features that perform implicit color normalization while the gain is higher for patch-based classification methods for classifying epithelium versus stroma.
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Book Review:
Review of "Practical Informatics for Cytopathology"
George G Birdsong
J Pathol Inform
2016, 7:16 (11 April 2016)
DOI
:10.4103/2153-3539.179909
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Research Article:
Quantitative analysis of myocardial tissue with digital autofluorescence microscopy
Thomas Jensen, Henrik Holten-Rossing, Ida M H Svendsen, Christina Jacobsen, Ben Vainer
J Pathol Inform
2016, 7:15 (11 April 2016)
DOI
:10.4103/2153-3539.179908
PMID
:27141321
Background:
The opportunity offered by whole slide scanners of automated histological analysis implies an ever increasing importance of digital pathology. To go beyond the importance of conventional pathology, however, digital pathology may need a basic histological starting point similar to that of hematoxylin and eosin staining in conventional pathology. This study presents an automated fluorescence-based microscopy approach providing highly detailed morphological data from unstained microsections. This data may provide a basic histological starting point from which further digital analysis including staining may benefit.
Methods:
This study explores the inherent tissue fluorescence, also known as autofluorescence, as a mean to quantitate cardiac tissue components in histological microsections. Data acquisition using a commercially available whole slide scanner and an image-based quantitation algorithm are presented.
Results:
It is shown that the autofluorescence intensity of unstained microsections at two different wavelengths is a suitable starting point for automated digital analysis of myocytes, fibrous tissue, lipofuscin, and the extracellular compartment. The output of the method is absolute quantitation along with accurate outlines of above-mentioned components. The digital quantitations are verified by comparison to point grid quantitations performed on the microsections after Van Gieson staining.
Conclusion:
The presented method is amply described as a prestain multicomponent quantitation and outlining tool for histological sections of cardiac tissue. The main perspective is the opportunity for combination with digital analysis of stained microsections, for which the method may provide an accurate digital framework.
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Original Article:
Perceptions of pathology informatics by non-informaticist pathologists and trainees
Addie Walker, Christopher Garcia, Jason M Baron, Thomas M Gudewicz, John R Gilbertson, Walter H Henricks, Roy E Lee
J Pathol Inform
2016, 7:14 (11 April 2016)
DOI
:10.4103/2153-3539.179904
PMID
:27141320
Background:
Although pathology informatics (PI) is essential to modern pathology practice, the field is often poorly understood. Pathologists who have received little to no exposure to informatics, either in training or in practice, may not recognize the roles that informatics serves in pathology. The purpose of this study was to characterize perceptions of PI by noninformatics-oriented pathologists and to do so at two large centers with differing informatics environments.
Methods:
Pathology trainees and staff at Cleveland Clinic (CC) and Massachusetts General Hospital (MGH) were surveyed. At MGH, pathology department leadership has promoted a pervasive informatics presence through practice, training, and research. At CC, PI efforts focus on production systems that serve a multi-site integrated health system and a reference laboratory, and on the development of applications oriented to department operations. The survey assessed perceived definition of PI, interest in PI, and perceived utility of PI.
Results:
The survey was completed by 107 noninformatics-oriented pathologists and trainees. A majority viewed informatics positively. Except among MGH trainees, confusion of PI with information technology (IT) and help desk services was prominent, even in those who indicated they understood informatics. Attendings and trainees indicated desire to learn more about PI. While most acknowledged that having some level of PI knowledge would be professionally useful and advantageous, only a minority plan to utilize it.
Conclusions:
Informatics is viewed positively by the majority of noninformatics pathologists at two large centers with differing informatics orientations. Differences in departmental informatics culture can be attributed to the varying perceptions of PI by different individuals. Incorrect perceptions exist, such as conflating PI with IT and help desk services, even among those who claim to understand PI. Further efforts by the PI community could address such misperceptions, which could help enable a better understanding of what PI is and is not, and potentially lead to increased acceptance by non-informaticist pathologists.
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Technical Note:
Pathology interface for the molecular analysis of tissue by mass spectrometry
Jeremy L Norris, Tina Tsui, Danielle B Gutierrez, Richard M Caprioli
J Pathol Inform
2016, 7:13 (11 April 2016)
DOI
:10.4103/2153-3539.179903
PMID
:27141319
Background:
Imaging mass spectrometry (IMS) generates molecular images directly from tissue sections to provide better diagnostic insights and expand the capabilities of clinical anatomic pathology. Although IMS technology has matured over recent years, the link between microscopy imaging currently used by pathologists and MS-based molecular imaging has not been established.
Methods:
We adapted the Vanderbilt University Tissue Core workflow for IMS into a web-based system that facilitates remote collaboration. The platform was designed to perform within acceptable web response times for viewing, annotating, and processing high resolution microscopy images.
Results:
We describe a microscopy-driven approach to tissue analysis by IMS.
Conclusion:
The Pathology Interface for Mass Spectrometry is designed to provide clinical access to IMS technology and deliver enhanced diagnostic value.
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Symposium:
Summary of third Nordic symposium on digital pathology
Claes Lundstrom, Marie Waltersson, Anders Persson, Darren Treanor
J Pathol Inform
2016, 7:12 (11 April 2016)
DOI
:10.4103/2153-3539.179902
PMID
:27141318
Cross-disciplinary and cross-sectorial collaboration is a key success factor for turning the promise of digital pathology into actual clinical benefits. The Nordic symposium on digital pathology (NDP) was created to promote knowledge exchange in this area, among stakeholders in health care, industry, and academia. This article is a summary of the third NDP symposium in Linkφping, Sweden. The Nordic experiences, including several hospitals using whole-slide imaging for substantial parts of their primary reviews, formed a fertile base for discussions among the 190 NDP attendees originating from 15 different countries. This summary also contains results from a survey on adoption and validation aspects of clinical digital pathology use.
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© Journal of Pathology Informatics | Published by Wolters Kluwer -
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Online since 10
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