A framework for optimising the radiographic technique in digital X-ray imaging
- 1. Multi-Modality Imaging Laboratory, Duke Univ. Medical Center, Durham, NC 27710 (United States)
- 2. Dept. of Physics, Duke Univ. Medical Center, Durham, NC 27710 (United States)
- 3. Dept. of Radiology, Duke Univ. Medical Center, Durham, NC 27710 (United States)
- 4. Duke Advanced Imaging Laboratories, Duke Univ. Medical Center, Durham, NC 27710 (United States)
Description
The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possible by rapid digital image acquisition. However, this transition has taken place largely without optimising the radiographic technique used to acquire the images. This paper proposes a framework for optimising the acquisition of digital X-ray images. The proposed approach is based on the signal and noise characteristics of the digital images and the applied exposure. Signal is defined, based on the clinical task involved in an imaging application, as the difference between the detector signal with and without a target present against a representative background. Noise is determined from the noise properties of uniformly acquired images of the background, taking into consideration the absorption properties of the detector. Incident exposure is estimated or otherwise measured free in air, and converted to dose. The main figure of merit (FOM) for optimisation is defined as the signal-difference-to-noise ratio (SdNR) squared per unit exposure or (more preferably) dose. This paper highlights three specific technique optimisation studies that used this approach to optimise the radiographic technique for digital chest and breast applications. In the first study, which was focused on chest radiography with a CsI flat-panel detector, a range of kV p (50-150) and filtration (Z = 13-82) were examined in terms of their associated FOM as well as soft tissue to bone contrast, a factor of importance in digital chest radiography. The results indicated that additive Cu filtration can improve image quality. A second study in digital mammography using a selenium direct flat-panel detector indicated improved SdNR per unit exposure with the use of a tungsten target and a rhodium filter than conventional molybdenum target/molybdenum filter techniques. Finally, a third study focusing on cone-beam computed tomography of the breast using a CsI flat-panel detector indicated that high Z filtration of a tungsten target X-ray beam can notably improve the signal and noise characteristics of the image. The general findings highlight the fact that the techniques that are conventionally assumed to be optimum may need to be revisited for digital radiography. (authors)
Availability note (English)
Available from doi: http://dx.doi.org/10.1093/rpd/nch562Additional details
Identifiers
- DOI
- 10.1093/rpd/nch562;
Publishing Information
- Journal Title
- Radiation Protection Dosimetry
- Journal Volume
- 114
- Journal Issue
- 1-3
- Journal Page Range
- p. 220-229
- ISSN
- 0144-8420
Conference
- Title
- 2. Malmoe Conference on Medical X-Ray Imaging - Optimisation strategies in medical X-ray imaging
- Dates
- 23-25 Apr 2004
- Place
- Malmoe (Sweden)
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- France
- INIS RN
- 44035797
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE; S61: RADIATION PROTECTION AND DOSIMETRY;
- Resource subtype / Literary indicator
- Conference
- Descriptors DEI
- BACKGROUND NOISE; BIOMEDICAL RADIOGRAPHY; CHEST; COMPUTERIZED TOMOGRAPHY; IMAGES; MAMMARY GLANDS; MOLYBDENUM; RADIATION DOSES; SKELETON; TUNGSTEN; X RADIATION
- Descriptors DEC
- BODY; DIAGNOSTIC TECHNIQUES; DOSES; ELECTROMAGNETIC RADIATION; ELEMENTS; GLANDS; IONIZING RADIATIONS; MEDICINE; METALS; NOISE; NUCLEAR MEDICINE; ORGANS; RADIATIONS; RADIOLOGY; REFRACTORY METALS; TOMOGRAPHY; TRANSITION ELEMENTS
Optional Information
- Notes
- 19 refs