Taskbased Modeling Of A 5K Ultrahighresolution Medical Imaging System For Digital Breast Tomosynthesis

• doi: 10.1109/TMI.2017.2695982
• title: Task-Based Modeling of a 5k Ultra-High-Resolution Medical Imaging System for Digital Breast Tomosynthesis
• publisher: IEEE
• isbn:
• issn: 1558-254X
• rank: 3730
• access_type: LOCKED
• content_type: Journals
• abstract: High-resolution, low-noise X-ray detectors based on CMOS active pixel sensor (APS) technology have demonstrated superior imaging performance for digital breast tomosynthesis (DBT). This paper presents a task-based model for a high-resolution medical imaging system to evaluate its ability to detect simulated microcalcifications and masses as lesions for breast cancer. A 3-D cascaded system analysis for a 50-μm pixel pitch CMOS APS X-ray detector was integrated with an object task function, a medical imaging display model, and the human eye contrast sensitivity function to calculate the detectability index and area under the ROC curve (AUC). It was demonstrated that the display pixel pitch and zoom factor should be optimized to improve the AUC for detecting small microcalcifications. In addition, detector electronic noise of smaller than 300 e- and a high display maximum luminance (>1000 cd/cm2) are desirable to distinguish microcalcifications of 150 μm in size. For low contrast mass detection, a medical imaging display with a minimum of 12-bit gray levels is recommended to realize accurate luminance levels. A wide projection angle range of greater than ±30° in combination with the image gray level magnification could improve the mass detectability especially when the anatomical background noise is high. On the other hand, a narrower projection angle range below ±20° can improve the small, high contrast object detection. Due to the low mass contrast and luminance, the ambient luminance should be controlled below 5 cd/m2. Task-based modeling provides important firsthand imaging performance of the high-resolution CMOS-based medical imaging system that is still at early stage development for DBT. The modeling results could guide the prototype design and clinical studies in the future.
• article_number: 7904709
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7904709
• html_url: https://ieeexplore.ieee.org/document/7904709/
• abstract_url: https://ieeexplore.ieee.org/document/7904709/
• publication_title: IEEE Transactions on Medical Imaging
• conference_location:
• conference_dates:
• publication_number: 42
• is_number: 8022994
• publication_year: 2017
• publication_date: Sept. 2017
• start_page: 1820
• end_page: 1831
• citing_paper_count: 4
• citing_patent_count: 0
• download_count: 475
• insert_date: 20170419
• index_terms:
  • ieee_terms:
    • Three-dimensional displays
    • Detectors
    • Biomedical imaging
    • Observers
    • Two dimensional displays
    • Semiconductor device modeling
    • X-ray detectors
  • author_terms:
    • Task-based modeling
    • CMOS X-ray detector
    • medical imaging display
    • model observers
    • tomosynthesis
  • dynamic_index_terms:
    • Medical Imaging
    • Clinical Imaging
    • Diagnostic Imaging
    • Medical Systems
    • Medical Imaging Systems
    • Digital Tomosynthesis
    • Digital Breast Tomosynthesis
    • High-resolution
    • Receiver Operating Characteristic Curve
    • ROC Curve
    • Grayscale
    • Greyscale
    • Gray Level
    • Background Noise
    • Ambient Noise
    • Object Detection
    • High Contrast
    • Human Eye
    • Low Contrast
    • Mass Detector
    • Contrast Sensitivity
    • Electrical Noise
    • Electronic Noise
    • X-ray Detector
    • Contrast Objective
    • Projection Angle
    • Noise Power Spectrum
    • Modulation Transfer Function
    • Optical Transfer Function
    • Linear Attenuation Coefficient
    • Internal Noise
    • Spatial Domain
    • Low Noise
    • Angular Frequency
    • Human Observers
    • Imaging Tasks
    • Cycle Frequency
• authors:
  • Author Name: Chumin Zhao
    Affiliation: Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
    Author URL: https://ieeexplore.ieee.org/author/37085888499
    ID: 37085888499
    Order: 1
    Author Affiliations:
    • Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
  • Author Name: Jerzy Kanicki
    Affiliation: Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
    Author URL: https://ieeexplore.ieee.org/author/37271208200
    ID: 37271208200
    Order: 2
    Author Affiliations:
    • Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA

Image Sensor

• sensor_type: CMOS active pixel sensor (APS)
• resolution: 5120 x 5248
• dynamic_range: Not specified
• pixel_size: 50 µm
• dark_current: 150 to 300 e- (electrons) per second

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

• noise: Below 300 e- for effective detection of microcalcifications (150 µm)

Applications & Benefits

• cell_imaging: Digital breast tomosynthesis (DBT) for detecting breast cancer lesions such as microcalcifications and masses
• benefits: Higher detection accuracy due to low electronic noise and high resolution, contributing to improved breast cancer screening.

Supporting Organizations

• supported_by: University of Michigan EECS Department, collaborations with various authors and researchers

Manuscript Details

• publication_date: Sept. 2017

Relevancy Score

• score: 9
• missing_fields:
  • dynamic_range
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption

Processed JSON Filename

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