Mahmoud Ismail

Bio: Mahmoud Ismail is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: DICOM & Metadata repository. The author has an hindex of 3, co-authored 5 publications receiving 32 citations.

3D-guided CT reconstruction using time-of-flight camera

Abstract: We propose the use of a time-of-flight (TOF) camera to obtain the patient's body contour in 3D guided imaging reconstruction scheme in CT and C-arm imaging systems with truncated projection. In addition to pixel intensity, a TOF camera provides the 3D coordinates of each point in the captured scene with respect to the camera coordinates. Information from the TOF camera was used to obtain a digitized surface of the patient's body. The digitization points are transformed to X-Ray detector coordinates by registering the two coordinate systems. A set of points corresponding to the slice of interest are segmented to form a 2D contour of the body surface. Radon transform is applied to the contour to generate the 'trust region' for the projection data. The generated 'trust region' is integrated as an input to augment the projection data. It is used to estimate the truncated, unmeasured projections using linear interpolation. Finally the image is reconstructed using the combination of the estimated and the measured projection data. The proposed method is evaluated using a physical phantom. Projection data for the phantom were obtained using a C-arm system. Significant improvement in the reconstructed image quality near the truncation edges was observed using the proposed method as compared to that without truncation correction. This work shows that the proposed 3D guided CT image reconstruction using a TOF camera represents a feasible solution to the projection data truncation problem.

Multi-series DICOM: an Extension of DICOM That Stores a Whole Study in a Single Object

Abstract: Today, most medical images are stored as a set of single-frame composite Digital Imaging and Communications in Medicine (DICOM) objects that contain the four levels of the DICOM information model—patient, study, series, and instance. Although DICOM addresses most of the issues related to medical image archiving, it has some limitations. Replicating the header information with each DICOM object increases the study size and the parsing overhead. Multi-frame DICOM (MFD) was developed to address this, among other issues. The MFD combines all DICOM objects belonging to a series into a single DICOM object. Hence, the series-level attributes are normalized, and the amount of header data repetition is reduced. In this paper, multi-series DICOM (MSD) is introduced as a potential extension to the DICOM standard that allows faster parsing, transmission, and storage of studies. MSD extends the MFD de-duplication of series-level attributes to study-level attributes. A single DICOM object that stores the whole study is proposed. An efficient algorithm, called the one-pass de-duplication algorithm, was developed to find and eliminate the replicated data elements within the study. A group of experiments were done that evaluate MSD and the one-pass de-duplication algorithm performance. The experiments show that MSD significantly reduces the amount of data repetition and decreases the time required to read and parse DICOM studies. MSD is one possible solution that addresses the DICOM limitations regarding header information repetition.

Fast processing of digital imaging and communications in medicine (DICOM) metadata using multiseries DICOM format.

Abstract: The digital imaging and communications in medicine (DICOM) information model combines pixel data and its metadata in a single object. There are user scenarios that only need metadata manipulation, such as deidentification and study migration. Most picture archiving and communication system use a database to store and update the metadata rather than updating the raw DICOM files themselves. The multiseries DICOM (MSD) format separates metadata from pixel data and eliminates duplicate attributes. This work promotes storing DICOM studies in MSD format to reduce the metadata processing time. A set of experiments are performed that update the metadata of a set of DICOM studies for deidentification and migration. The studies are stored in both the traditional single frame DICOM (SFD) format and the MSD format. The results show that it is faster to update studies’ metadata in MSD format than in SFD format because the bulk data is separated in MSD and is not retrieved from the storage system. In addition, it is space efficient to store the deidentified studies in MSD format as it shares the same bulk data object with the original study. In summary, separation of metadata from pixel data using the MSD format provides fast metadata access and speeds up applications that process only the metadata.

Separation of metadata and bulkdata to speed DICOM tag morphing

Abstract: Most medical images are archived and transmitted using the DICOM format. The DICOM information model combines image pixel data and associated metadata into a single object. It is not possible to access the metadata separately from the pixel data. However, there are important use cases that only need access to metadata, and the DICOM format increases the running time of those use cases. Tag morphing is an example of one such use case. Tag or attribute morphing includes insertion, deletion, or modification of one or more of the metadata attributes in a study. It is typically used for order reconciliation on study acquisition or to localize the Issuer of Patient ID and the Patient ID attributes when data from one Medical Record Number (MRN) domain is transferred to or displayed in a different domain. This work uses the Multi-Series DICOM (MSD) format to reduce the time required for tag morphing. The MSD format separates metadata from pixel data, and at the same time eliminates duplicate attributes. MSD stores studies using two files rather than in many single frame files typical of DICOM. The first file contains the de-duplicated study metadata, and the second contains pixel data and other bulkdata. A set of experiments were performed where metadata updates were applied to a set of DICOM studies stored in both the traditional Single Frame DICOM (SFD) format and the MSD format. The time required to perform the updates was recorded for each format. The results show that tag morphing is, on average, more than eight times faster in MSD format.

Transmission of DICOM studies using Multi-Series DICOM format

Abstract: The DICOM standard defines the application layer network protocol used to send and receive medical images. DICOM is defined on top of TCP. DICOM addresses many issues associated with medical image transmission; however, sending and receiving large studies is inefficient because they are transmitted one object at a time. The Multi-Series DICOM (MSD) format has been introduced as a solution to this problem. It can store an entire study in a single object. In addition, the metadata information in the MSD object is free of repetition. In this work, the performance of sending and receiving DICOM studies as MSD objects is investigated. A set of DICOM studies is stored in two formats, traditional Single-Frame DICOM (SFD) and MSD. The times required to send the studies in both formats synchronously and asynchronously are measured. The results show that there is a significant reduction in the time required to synchronously send the studies in the MSD format compared to the SFD format and a small improvement when sending asynchronously. Sending studies synchronously in the SFD format results in a delay waiting for the acknowledgement for each DICOM object sent before sending subsequent ones. With the asynchronous approach, the time reduction is a direct result of the difference in metadata size between the SFD and MSD formats and the lower number of acknowledgements sent back from the receiving application entity to the sender. The results show that it is more efficient to send DICOM studies as MSD objects whether synchronously or asynchronously.

An ultrasound system with stereo image guidance or tracking

Abstract: An image-guided ultrasound system may include an ultrasound probe, a display configured to communicate with the ultrasound probe to receive ultrasound signals to display images from the ultrasound probe, and an imaging device that may be attached to or integral with the ultrasound probe and configured to communicate with the display to display information derived from images from the imaging device. The imaging device may include a stabilization assembly, an imaging device assembly physically coupled to the stabilization assembly, a plurality of light-sensitive devices physically coupled to the stabilization assembly, and a memory unit physically coupled to the imaging device assembly, the memory unit configured to store calibration or usage information for the image-guided ultrasound system.

Navigation with Local Sensors in Handheld 3D Ultrasound — Initial in-vivo Experience

Abstract: Handheld ultrasound is useful for intra-operative imaging, but requires additional tracking hardware to be useful in navigated intervention settings, such as biopsies, ablation therapy, injections etc. Unlike common probe-andneedle tracking approaches involving global or local tracking, we propose to use a bracket with a combination of very low-cost local sensors - cameras with projectors, optical mice and accelerometers - to reconstruct patient surfaces, needle poses, and the probe trajectory with multiple degrees of freedom, but no global tracking overhead. We report our experiences from a rst series of benchtop and in-vivo human volunteer experiments.

MR Imaging-Histology Correlation by Tailored 3D-Printed Slicer in Oncological Assessment.

Abstract: 3D printing and reverse engineering are innovative technologies that are revolutionizing scientific research in the health sciences and related clinical practice. Such technologies are able to improve the development of various custom-made medical devices while also lowering design and production costs. Recent advances allow the printing of particularly complex prototypes whose geometry is drawn from precise computer models designed on in vivo imaging data. This review summarizes a new method for histological sample processing (applicable to e.g., the brain, prostate, liver, and renal mass) which employs a personalized mold developed from diagnostic images through computer-aided design software and 3D printing. Through positioning the custom mold in a coherent manner with respect to the organ of interest (as delineated by in vivo imaging data), the cutting instrument can be precisely guided in order to obtain blocks of tissue which correspond with high accuracy to the slices imaged. This approach appeared crucial for validation of new quantitative imaging tools, for an accurate imaging-histopathological correlation and for the assessment of radiogenomic features extracted from oncological lesions. The aim of this review is to define and describe 3D printing technologies which are applicable to oncological assessment and slicer design, highlighting the radiological and pathological perspective as well as recent applications of this approach for the histological validation of and correlation with MR images.

Interior micro-CT with an offset detector

Abstract: Purpose: The size of field-of-view (FOV) of a microcomputed tomography (CT) system can be increased by offsetting the detector. The increased FOV is beneficial in many applications. All prior investigations, however, have been focused to the case in which the increased FOV after offset-detector acquisition can cover the transaxial extent of an object fully. Here, the authors studied a new problem where the FOV of a micro-CT system, although increased after offset-detector acquisition, still covers an interior region-of-interest (ROI) within the object. Methods: An interior-ROI-oriented micro-CT scan with an offset detector poses a difficult reconstruction problem, which is caused by both detector offset and projection truncation. Using the projection completion techniques, the authors first extended three previous reconstruction methods from offset-detector micro-CT to offset-detector interior micro-CT. The authors then proposed a novel method which combines two of the extended methods using a frequency split technique. The authors tested the four methods with phantom simulations at 9.4%, 18.8%, 28.2%, and 37.6% detector offset. The authors also applied these methods to physical phantom datasets acquired at the same amounts of detector offset from a customized micro-CT system. Results: When the detector offset was small, all reconstruction methods showed good image quality. At large detector offset, the three extended methods gave either visible shading artifacts or high deviation of pixel value, while the authors’ proposed method demonstrated no visible artifacts and minimal deviation of pixel value in both the numerical simulations and physical experiments. Conclusions: For an interior micro-CT with an offset detector, the three extended reconstruction methods can perform well at a small detector offset but show strong artifacts at a large detector offset. When the detector offset is large, the authors’ proposed reconstruction method can outperform the three extended reconstruction methods by suppressing artifacts and maintaining pixel values.