DICOMweb™: Background and Application of the Web Standard for Medical Imaging

Genereaux, Brad; Dennison, Donald K.; Ho, Kinson; Horn, Robert J; Silver, Elliot L.; O'Donnell, Kevin; Kahn, Charles Η.

doi:10.1007/s10278-018-0073-z

Cited by 33 publications

(18 citation statements)

References 1 publication

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“…Current standards that can be adapted to serve this function of the PACS / RIS monitor include the DICOM/IHE Instance Availability Notification (IAN) (7) . DICOMweb standards can be used to support offsite image analysis, which would be limited by more traditional DICOM transfer methods (8) .…”

Section: Discussionmentioning

confidence: 99%

Building Blocks for Integrating Image Analysis Algorithms into a Clinical Workflow

Juluru

Shih

Elnajjar

et al. 2020

Preprint

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Purpose Starting from a broad-based needs assessment and utilizing an image analysis algorithm (IAA) developed at our institution, the purpose of this study was to define generalizable building blocks necessary for the integration of any IAA into a clinical practice. Methods An IAA was developed in our institution to process lymphoscintigraphy exams. A team of radiologists defined a set of building blocks for integration of this IAA into clinical workflow. The building blocks served the following roles: (1) Timely delivery of images to the IAA, (2) quality control, (3) IAA results processing, (4) results presentation & delivery, (5) IAA error correction, (6) system performance monitoring, and (7) active learning. Utilizing these modules, the lymphoscintigraphy IAA was integrated into the clinical workflow at our institution. System performance was tested over a 1 month period, including assessment of number of exams processed and delivered, and error rates and corrections. Results From June 26-July 27, 2019, the building blocks were used to integrate IAA results from 132 lymphoscintigraphy exams into the clinical workflow, representing 100% of the exams performed during the time period. The system enabled radiologists to correct 21 of the IAA results. All results and corrections were successfully stored in a database. A dashboard allowed the development team to monitor system performance in real-time. Conclusions We describe seven building blocks that optimize the integration of IAAs into clinical workflow. The implementation of these building blocks in this study can be used to inform development of more robust, standards-based solutions.

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Section: Discussionmentioning

confidence: 99%

Building Blocks for Integrating Image Analysis Algorithms into a Clinical Workflow

Juluru

Shih

Elnajjar

et al. 2020

Preprint

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“…[ 54 ] Recently, RESTful web services have been made available for storage, query, and retrieval over HTTP protocol. [ 75 ] We decided to use DICOM PS3.18 RESTful web services (DICOMweb™) and investigated the compatibility of VL Whole Slide Microscopy Image instances with existing DICOM archives [ Figure 6a ]. A key feature of DICOMweb is that it allows efficient access to subsets of server-side DICOM data sets from thin clients, such as smartphones, and tablet computers.…”

Section: R Esultsmentioning

confidence: 99%

Implementing the DICOM Standard for Digital Pathology

Herrmann¹,

Clunie²,

Fedorov

et al. 2018

Journal of Pathology Informatics

101

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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 aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network.Methods:We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. We generated the files using image data from four vendor-specific image file formats and clinical metadata from two departments with different laboratory information systems. We validated the generated DICOM files using recognized DICOM validation tools and measured encoding, storage, and access efficiency for three image compression methods. Finally, we evaluated storing, querying, and retrieving data over the web using existing DICOM archive software.Results:Whole slide image data can be encoded together with relevant patient and specimen-related metadata as DICOM objects. These objects can be accessed efficiently from files or through RESTful web services using existing software implementations. Performance measurements show that the choice of image compression method has a major impact on data access efficiency. For lossy compression, JPEG achieves the fastest compression/decompression rates. For lossless compression, JPEG-LS significantly outperforms JPEG 2000 with respect to data encoding and decoding speed.Conclusion:Implementation of DICOM allows efficient access to image data as well as associated metadata. By leveraging a wealth of existing infrastructure solutions, the use of DICOM facilitates enterprise integration and data exchange for digital pathology.

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“…Digital medical images could be generated form diagnostic modalities such as Ultrasound, Nuclear Medicine, digital radiography, X-ray and hospital information system, etc. [24]. Nowadays, DICOM is used in radiology, cardiology imaging, radiotherapy device, ophthalmology, and dentistry.…”

Section: Key Features Of Dicom File Formatmentioning

confidence: 99%

“…Nowadays, DICOM is used in radiology, cardiology imaging, radiotherapy device, ophthalmology, and dentistry. In other words, DICOM is widely used in most of the healthcare messaging standards in the world [24]. The digital watermarking techniques should employ necessary steps so that the quality of medical images are not degraded and are still conform with Digital Imaging and Communication in Medicine (DICOM) format.…”

Section: Key Features Of Dicom File Formatmentioning

confidence: 99%

Reversible Data Hiding for DICOM Image Using Lifting and Companding

Phadikar

Jana²,

Mandal

2019

Cryptography

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In this work, a reversible watermarking technique is proposed for DICOM (Digital Imaging and Communications in Medicine) image that offers high embedding capacity (payload), security and fidelity of the watermarked image. The goal is achieved by embedding watermark based on companding in lifting based discrete wavelet transform (DWT) domain. In the embedding process, the companding technique is used to increase the data hiding capacity. On the other hand, a simple linear function is used in companding to make the scheme easy to implement, and content dependant watermark is used to make the scheme robust to collusion operation. Moreover, unlike previously proposed reversible watermarking techniques, this novel approach does not embed the location map in the host image that ultimately helps to achieve high fidelity of the watermarked image. The advantage of the proposed scheme is demonstrated by simulation results and also compared with selected other related schemes.

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DICOMweb™: Background and Application of the Web Standard for Medical Imaging

Cited by 33 publications

References 1 publication

Building Blocks for Integrating Image Analysis Algorithms into a Clinical Workflow

Building Blocks for Integrating Image Analysis Algorithms into a Clinical Workflow

Implementing the DICOM Standard for Digital Pathology

Reversible Data Hiding for DICOM Image Using Lifting and Companding

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