An adaptable navigation strategy for Virtual Microscopy from mobile platforms

Corredor, Germán; Romero, Eduardo; Iregui, Marcela

doi:10.1016/j.jbi.2015.01.013

Cited by 13 publications

(6 citation statements)

References 34 publications

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“…From Columbia, a study (n = 20) evaluated the performance of VM from mobile platforms. 126 Two expert pathologists successfully reviewed 20 VSs on mobile platforms. The important findings from this research point to the importance of a smart decoding strategy, flexible data management, and an architecture that adapts to device resources and network bandwidth.…”

Section: Telepathology Evidence: Feasibility and Acceptancementioning

confidence: 99%

The Empirical Foundations of Telepathology: Evidence of Feasibility and Intermediate Effects

Bashshur

Krupiński

Weinstein

et al. 2017

Telemedicine and e-Health

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The evidence regarding feasibility/acceptance of telepathology and related information technology applications has been well documented for several decades. The majority of evidentiary studies focused on intermediate outcomes, as indicated by comparability between telepathology and conventional light microscopy. A consistent trend of concordance between the two modalities was observed in terms of diagnostic accuracy and reliability. Additional benefits include use of telepathology and whole slide imaging for teaching, research, and outreach to resource-limited countries. Challenges still exist, however, in terms of use of telepathology as an effective diagnostic modality in clinical practice.

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Section: Telepathology Evidence: Feasibility and Acceptancementioning

confidence: 99%

The Empirical Foundations of Telepathology: Evidence of Feasibility and Intermediate Effects

Bashshur

Krupiński

Weinstein

et al. 2017

Telemedicine and e-Health

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“…Of note, the use of smaller screen sizes has gained increased attention with the growth of mobile devices in digital pathology. [ 51 52 53 ] While both smartphones and tablets have seen considerable technological advancements in display technology, one must remember that mobile devices should not be viewed as just another display, but instead as an app ecosystem, platform, and overall, an all-in-one device. As such, all aspects of a mobile device must be considered when considering them for specific digital pathology use cases, including computing power, network connectivity, storage capacity, battery life, security capabilities, input methods, operating system, and app platform/availability, in addition to the size and quality of the included display.…”

Section: Ommon D Isplay S mentioning

confidence: 99%

Display Characteristics and Their Impact on Digital Pathology: A Current Review of Pathologists’ Future “Microscope”

Abel

Ouillette

Williams

et al. 2020

Journal of Pathology Informatics

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Digital displays (monitors) are an indispensable component of a pathologists’ daily workflow, from writing reports, viewing whole-slide images, or browsing the Internet. Due to a paucity of literature and experience surrounding display use and standardization in pathology, the Food and Drug Administration's (FDA) has currently restricted FDA-cleared whole-slide imaging systems to a specific model of display for each system, which at this time consists of only medical-grade (MG) displays. Further, given that a pathologists’ display will essentially become their new surrogate “microscope,” it becomes exceedingly important that all pathologists have a basic understanding of fundamental display properties and their functional consequences. This review seeks to: (a) define and summarize the current and emerging display technology, terminology, features, and regulation as they pertain to pathologists and review the current literature on the impact of different display types (e.g. MG vs. consumer off the shelf vs. professional grade) on pathologists’ diagnostic performance and (b) discuss the impact of the recent digital pathology device componentization and the coronavirus disease 2019 public emergency on the pixel pathway and display use for remote digital pathology. Display technology has changed dramatically over the past 20 years and continues to change at a rapid rate. There is a paucity of published studies to date that investigate how display type affects pathologist performance, with more research necessary in order to develop standards and minimum specifications for displays in digital pathology. Given the complexity of modern displays, pathologists must become better informed regarding display technology if they wish to have more choice over their future “microscopes.”

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“…[41][42][43] However, the JPEG2000 (J2K) standard, characterized by a natural multiresolution decomposition, lossless compression, and random spatial access, 44,45 better suits the requirements for this type of interaction. In Ref.…”

Section: Visualization Strategy and Tracking Systemmentioning

confidence: 99%

“…In Ref. 43, the J2K model was adapted to improve the dynamic interaction between WSIs and a custom virtual microscope was enabled to run on small devices such as smartphones or tablets. The principle of this navigation is that the client requests ROIs instead of the entire image, thereby reducing the amount of information requested.…”

Section: Visualization Strategy and Tracking Systemmentioning

confidence: 99%

Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features

et al. 2017

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Abstract. Computational histomorphometric approaches typically use low-level image features for building machine learning classifiers. However, these approaches usually ignore high-level expert knowledge. A computational model (M_im) combines low-, mid-, and high-level image information to predict the likelihood of cancer in whole slide images. Handcrafted low-and mid-level features are computed from area, color, and spatial nuclei distributions. High-level information is implicitly captured from the recorded navigations of pathologists while exploring whole slide images during diagnostic tasks. This model was validated by predicting the presence of cancer in a set of unseen fields of view. The available database was composed of 24 cases of basal-cell carcinoma, from which 17 served to estimate the model parameters and the remaining 7 comprised the evaluation set. A total of 274 fields of view of size 1024 × 1024 pixels were extracted from the evaluation set. Then 176 patches from this set were used to train a support vector machine classifier to predict the presence of cancer on a patch-by-patch basis while the remaining 98 image patches were used for independent testing, ensuring that the training and test sets do not comprise patches from the same patient. A baseline model (M_ex) estimated the cancer likelihood for each of the image patches. M_ex uses the same visual features as M_im, but its weights are estimated from nuclei manually labeled as cancerous or noncancerous by a pathologist. M_im achieved an accuracy of 74.49% and an F -measure of 80.31%, while M_ex yielded corresponding accuracy and F-measures of 73.47% and 77.97%, respectively.

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An adaptable navigation strategy for Virtual Microscopy from mobile platforms

Cited by 13 publications

References 34 publications

The Empirical Foundations of Telepathology: Evidence of Feasibility and Intermediate Effects

The Empirical Foundations of Telepathology: Evidence of Feasibility and Intermediate Effects

Display Characteristics and Their Impact on Digital Pathology: A Current Review of Pathologists’ Future “Microscope”

Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features

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