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Publications (110)
The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and div...
Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating their downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve acceptable performance and thus can be used to autom...
Purpose: De-identification of cancer imaging data is vitally important for data sharing and the advancement of research, however it is a time consuming and complex process that limits access to new cancer data sets such as those shared through NCI's Imaging Data Commons (IDC), built on the Google Cloud Platform (GCP). Our research demonstrates how...
This report addresses the technical aspects of de-identification of medical images of human subjects and biospecimens, such that re-identification risk of ethical, moral, and legal concern is sufficiently reduced to allow unrestricted public sharing for any purpose, regardless of the jurisdiction of the source and distribution sites. All medical im...
The exchange of large and complex slide microscopy imaging data in biomedical research and pathology practice is impeded by a lack of data standardization and interoperability, which is detrimental to the reproducibility of scientific findings and clinical integration of technological innovations. We introduce Slim, an open-source, web-based slide...
This report addresses the technical aspects of de-identification of medical images of human subjects and biospecimens, such that re-identification risk of ethical, moral, and legal concern is sufficiently reduced to allow unrestricted public sharing for any purpose, regardless of the jurisdiction of the source and distribution sites. All medical im...
Objective: Reproducibility is critical for translating machine learning-based (ML) solutions in computational pathology (CompPath) into practice. However, an increasing number of studies report difficulties in reproducing ML results. The NCI Imaging Data Commons (IDC) is a public repository of >120 cancer image collections, including >38,000 whole-...
Machine learning (ML) is revolutionizing image-based diagnostics in pathology and radiology. ML models have shown promising results in research settings, but the lack of interoperability between ML systems and enterprise medical imaging systems has been a major barrier for clinical integration and evaluation. The DICOM ® standard specifies informat...
Despite technological advances in the analysis of digital images for medical consultations, many health information systems lack the ability to correlate textual descriptions of image findings linked to the actual images. Images and reports often reside in separate silos in the medical record throughout the process of image viewing, report authorin...
The ability to exchange and use microscopy data is critical for biomedical research, but interoperable tools are currently lacking. Slim is an open-source web viewer that implements the Digital Imaging and Communications in Medicine (DICOM) standard to enable interactive visualization and annotation of brightfield and multiplexed immunofluorescence...
Purpose/Objective(s)
National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a cloud-based data science infrastructure. Imaging Data Commons (IDC) is a component of CRDC supported by the Cancer Moonshot™, which aims to enable access and exploration of de-identified imaging data, and to support integrated analyses with...
This white paper describes the technical details of best practices for coordinate-based geometric description of planar annotations encoded in DICOM Structured Reports (SR) for communicating user and machine created annotations about images, including quantitative measurements and categorical statements about regions of interest and other image-rel...
The National Cancer Institute (NCI) Cancer Research Data Commons (CRDC) aims to establish a national cloud-based data science infrastructure. Imaging Data Commons (IDC) is a new component of CRDC supported by the Cancer Moonshot. The goal of IDC is to enable a broad spectrum of cancer researchers, with and without imaging expertise, to easily acces...
Diagnostic and evidential static image, video clip, and sound multimedia are captured during routine clinical care in cardiology, dermatology, ophthalmology, pathology, physiatry, radiation oncology, radiology, endoscopic procedural specialties, and other medical disciplines. Providers typically describe the multimedia findings in contemporaneous e...
Machine learning is revolutionizing image-based diagnostics in pathology and radiology. ML models have shown promising results in research settings, but their lack of interoperability has been a major barrier for clinical integration and evaluation. The DICOM a standard specifies Information Object Definitions and Services for the representation an...
As part of the Open Source Initiative for Perfusion Imaging (OSIPI), the aim of this work is to develop guidelines for reporting of contrast-basedperfusion analysis in order to improve reproducibility, reusability and interoperability of perfusion analysis. For this, a perfusion analysis lexicon isdeveloped, which provides standardized nomenclature...
There is optimism that artificial intelligence (AI) will result in positive clinical outcomes, which is driving research and investment in the use of AI for skin disease. At present, AI for skin disease is embedded in research and development and not practiced widely in clinical dermatology. Clinical dermatology is also undergoing a technological t...
The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veteri...
A standard format for neurophysiology data is urgently needed to improve clinical care and promote research data exchange. Previous neurophysiology format standardization projects have provided valuable insights into how to accomplish the project. In medical imaging, the Digital Imaging and Communication in Medicine (DICOM) standard is widely adopt...
In order for enterprise imaging to be successful across a multitude of specialties, systems, and sites, standards are essential to categorize and classify imaging data. The HIMSS-SIIM Enterprise Imaging Community believes that the Digital Imaging Communications in Medicine (DICOM) Anatomic Region Sequence, or its equivalent in other data standards,...
The meaning of the term ‘abdomen’ has become increasingly ambiguous, as it has to satisfy the contemporary requirements of natural language discourse, literature, gross and radiological anatomy and its role in ontologies supporting electronic records and data modelling. It is critical that there is an agreed understanding of the semantics of the ab...
Published in Medical Physics, Vol. 47, No. 11
As the use of digital techniques in toxicologic pathology expands, challenges of scalability and interoperability come to the fore. Proprietary formats and closed single-vendor platforms prevail but depend on the availability and maintenance of multiformat conversion libraries. Expedient for small deployments, this is not sustainable at an industri...
In this paper we explore extending the concept of common cross-study Common Data Element concepts beyond simple demographics to cover disease-specific concepts relevant to imaging. We test interactively linking the resulting database to the associated images in a federated manner. We examine the use of existing standards, not only for terminology,...
Purpose:
The dataset contains annotations for lung nodules collected by the Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) stored as standard DICOM objects. The annotations accompany a collection of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers, and correspond to "nodules ≥ 3...
PURPOSE
We summarize Quantitative Imaging Informatics for Cancer Research (QIICR; U24 CA180918), one of the first projects funded by the National Cancer Institute (NCI) Informatics Technology for Cancer Research program.
METHODS
QIICR was motivated by the 3 use cases from the NCI Quantitative Imaging Network. 3D Slicer was selected as the platform...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
Purpose:
We summarize the AAPM TG248 Task Group report on interoperability assessment for the commissioning of medical imaging acquisition systems in order to bring needed attention to the value and role of quality assurance testing throughout the imaging chain.
Methods:
To guide the clinical physicist involved in commissioning of imaging system...
Multiparametric Magnetic Resonance Imaging (mpMRI) is widely used for characterizing prostate cancer. Standard of care use of mpMRI in clinic relies on visual interpretation of the images by an expert. mpMRI is also increasingly used as a quantitative imaging biomarker of the disease. Little is known about repeatability of such quantitative measure...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
The Lung Imaging Data Consortium and Image Database Resource Initiative (LIDC) conducted a multi-site reader study that produced a comprehensive database of Computed Tomography (CT) scans for over 1000 subjects annotated by multiple expert readers. The result is hosted in the LIDC-IDRI collection of The Cancer Imaging Archive (TCIA). Annotations th...
Background
Digital Imaging and Communications in Medicine (DICOM®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential...
Selected DICOM attributes for digital pathology
As digital pathology systems for clinical diagnostic work applications become mainstream, interoperability between these systems from different vendors becomes critical. For the first time, multiple digital pathology vendors have publicly revealed the use of the digital imaging and communications in medicine (DICOM) standard file format and network...
Imaging is increasingly being used in dermatology for documentation, diagnosis, and management of cutaneous disease. The lack of standards for dermatologic imaging is an impediment to clinical uptake. Standardization can occur in image acquisition, terminology, interoperability, and metadata. This paper presents the International Skin Imaging Colla...
Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number...
This white paper explores the technical challenges and solutions for acquiring (capturing) and managing enterprise images, particularly those involving visible light applications. The types of acquisition devices used for various general-purpose photography and specialized applications including dermatology, endoscopy, and anatomic pathology are re...
Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the establis...
Example of a populated TID 1500 imaging measurements container
Background and motivation for using DICOM to encode patient clinical information
QIICR PET SUV measurements of interest and their corresponding codes
QIICR Iowa Head and Neck Clinical Data DICOM SR Template
Background. Imaging biomarkers hold tremendous promise in the precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the estab...
Background. Imaging biomarkers hold tremendous promise in the precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the estab...
Background. Imaging biomarkers hold tremendous promise in the precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the estab...
Background. Imaging biomarkers hold tremendous promise in the precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the estab...
Though considerable progress has been made towards standardizing coded information in orders, worklists, images and structured reports for such things as anatomy, standardization of procedures codes, other than those used purely for reimbursement purposes, has been slow.
Most sites throughout the world still use locally defined codes for ordering...
Purpose:
To determine the extent of variations in computing standardized uptake value (SUV) by body weight (SUV(BW)) among different software packages and to propose a Digital Imaging and Communications in Medicine (DICOM) reference test object to ensure the standardization of SUV computation between medical image viewing workstations.
Materials...
Deidentification of medical images requires attention to both header information as well as the pixel data itself, in which burned-in text may be present. If the pixel data to be deidentified is stored in a compressed form, traditionally it is decompressed, identifying text is redacted, and if necessary, pixel data are recompressed. Decompression w...
To determine the variability of lesion size measurements in computed tomography data sets of patients imaged under a "no change" ("coffee break") condition and to determine the impact of two reading paradigms on measurement variability.
Using data sets from 32 non-small cell lung cancer patients scanned twice within 15 minutes ("no change"), measur...
This article summarizes the consensus reached at the Summit on Color in Medical Imaging held at the Food and Drug Administration (FDA) on May 8-9, 2013, co-sponsored by the FDA and ICC (International Color Consortium). The purpose of the meeting was to gather information on how color is currently handled by medical imaging systems to identify areas...
To estimate and statistically compare the bias and variance of radiologists measuring the size of spherical and complex synthetic nodules.
This study did not require the institutional review board approval. Six radiologists estimated the size of 10 synthetic nodules embedded within an anthropomorphic thorax phantom from computed tomography scans at...
LEARNING OBJECTIVES
1) Identify the importance of quantitative imaging principles in the setting of clinical trials. 2) identify the role of standards, including DICOM and others, in the successful application of quantitative imaging principles. 3) Analyze quantitative imaging techniques and apply this knowledge to protocol development in the setti...
Radiation Dose Structured ReportsMultiple diagnostic and/or interventional systems may expose a patient to radiation. The DICOM Information Object Definition (IOD) for these modalities may include acquisition data concerning the irradiation in each image instance produced. Yet, the aggregate irradiation information may not be easily determined from...
CONCLUSION Standard DICOM compression schemes, especially JPEG-LS, should be used for breast tomosynthesis data. BACKGROUND Availability & use of digital breast tomosynthesis is increasing & the size of the reconstructed images are an infrastructure challenge. Proprietary solutions are feasible, but it is desirable to re-use PACS standards & infras...
PURPOSE
To characterize the bias and variation in reader measurement of phantom nodule volumes in CT imagery from multiple scanners.
METHOD AND MATERIALS
The QIBA 1C project is a study of reader measurements of volume and longest in-slice diameter on 6 synthetic nodules placed in an anthropomorphic phantom. The phantom was imaged on 6 CT scanners:...
BACKGROUND
Use-cases for distribution of results for those without access to the authoring tool include referring physicians, external reviewers, public access, central review of site reads, review by regulators, & data mining. Either a standard format, or a review tool that is agnostic to the format is needed. A single universal format for results...
Data sharing is increasingly recognized as critical to cross-disciplinary research and to assuring scientific validity. Despite National Institutes of Health and National Science Foundation policies encouraging data sharing by grantees, little data sharing of clinical data has in fact occurred. A principal reason often given is the potential of ina...
PURPOSE
To determine the minimum detectable change in size of lung lesions by investigating 1D, 2D, and 3D measurement variability when patients are repeatedly imaged with CT under a “no change” (“coffee break”) condition.
METHOD AND MATERIALS
The CT datasets used were those of 32 non-small cell lung cancer patients scanned twice within 15 minutes...
Periodically an article appears in the scientific or medical literature describing some new reversible (lossless) or irreversible (lossy) image compression scheme, and either explicitly or buried within it, is a reference to the scheme’s applicability to medical image compression. It is no secret that the medical community makes extensive use of di...
The purpose of this work was to estimate bias in measuring the size of spherical and non-spherical lesions by radiologists using three sizing techniques under a variety of simulated lesion and reconstruction slice thickness conditions. We designed a reader study in which six radiologists estimated the size of 10 synthetic nodules of various sizes,...
LEARNING OBJECTIVES
1) Review integration challenges involved in Sharing Images on CD, DVD and USB. 2) Learn about the relevant data standards. 3) Understand how the IHE Portable Data for Imaging Profile (PDI), the IHE Import Reconciliation Workflow (IRWF) Profile and the IHE Basic Image Review (BIR) Profile address those challenges based on standa...