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EP-4740044-A1 - DENSITY CLUSTER IMAGING

EP4740044A1EP 4740044 A1EP4740044 A1EP 4740044A1EP-4740044-A1

Abstract

A method of improving a generated image obtained from a gamma camera used in medical imaging, the image improved by excluding low energy and scattered gamma rays from contributing to the generated image, the method comprising the steps of: • the gamma camera detecting gamma ray photons; • converting the detected gamma ray photons into one or more optical photons; • detecting the resultant optical photons on a photoactive surface; • processing the detected optical photons into a primary data array comprising pixels, wherein the pixels map the detection of the optical photons on the photoactive surface, wherein populated pixels correspond to the detection of the optical photons on the photoactive surface; • identifying clusters of populated pixels in the primary data array; • determining the density of the populated pixels in the identified clusters; • categorizing the clusters into high density clusters (clusters having a high density of populated pixels) and into low density clusters (clusters having a low density of populated pixels); • excluding the low density clusters from contributing to the generated image, these low density clusters corresponding to low energy and scattered gamma rays.

Inventors

  • WYLDE, George William

Assignees

  • Serac Imaging Systems LTD

Dates

Publication Date
20260513
Application Date
20240702

Claims (20)

  1. 1. A method of improving a generated image obtained from a gamma camera used in medical imaging, the image improved by excluding low energy and scattered gamma rays from contributing to the generated image, the method comprising the steps of: • the gamma camera detecting gamma ray photons; • converting the detected gamma ray photons into one or more optical photons; • detecting the resultant optical photons on a photoactive surface; • processing the detected optical photons into a primary data array comprising pixels, wherein the pixels map the detection of the optical photons on the photoactive surface, wherein populated pixels correspond to the detection of the optical photons on the photoactive surface; • identifying clusters of populated pixels in the primary data array; • determining the density of the populated pixels in the identified clusters; • categorizing the clusters into high density clusters (clusters having a high density of populated pixels) and into low density clusters (clusters having a low density of populated pixels); • excluding the low density clusters from contributing to the generated image, these low density clusters corresponding to low energy and scattered gamma rays.
  2. 2. The method of claim 1, wherein the method comprises assigning each high density cluster to the detection of a gamma ray photon, and using the gamma ray photon detection event to contribute to the generated image.
  3. 3. The method of claim 1 or 2, wherein the generated image comprises a single frame image, which may be combined with one or more additional single frame images to form a frame summed image.
  4. 4. The method of any one of the preceding claims, wherein the generated image is a frame summed image, the frame summed image being formed by combining two or more single frame images.
  5. 5. The method of any one of the preceding claims, wherein the step of excluding the low density clusters comprises the step of removing/zeroing the populated pixels from the primary data array that are not associated with the high density clusters, to form a secondary data array.
  6. 6. The method of claim 5, wherein the pixels in the secondary data array are averaged or combined with one or more adjacent pixels in the secondary data array (binning), to form an updated secondary data array to replace the previous secondary data array.
  7. 7. The method of claim 5 or 6, wherein each high density cluster in the secondary data array is assigned to a single populated pixel in a tertiary data array.
  8. 8. The method of claim 7, wherein pixels in the tertiary data array are averaged or combined with one or more adjacent pixels in the tertiary data array (binning), to form an updated tertiary data array to replace the previous tertiary data array.
  9. 9. The method of claim 7 or 8, wherein the position of each pixel in the tertiary data array maps to a relative position in the secondary data array, and where the position of the single populated pixel substantially corresponds to the centre of the assigning high density cluster.
  10. 10. The method of any one of claims 7 to 9, wherein a populated pixel in the tertiary data array corresponds to the detection of gamma ray photons by the gamma camera.
  11. 11. The method of any one of claims 7 to 10, wherein the populated pixels in the tertiary data array are used in forming the generated image.
  12. 12. The method of any one of claims 7 to 11, wherein unpopulated pixels in the tertiary data array correspond to the absence of the detection of gamma ray photons by the gamma camera.
  13. 13. The method of any one of the preceding claims, wherein a kernel is used to identify the clusters in the primary data array.
  14. 14. The method of claim 13, wherein the clusters identified by the kernel are categorized as having a high density of populated pixels, or as having a low density of populated pixels.
  15. 15. The method of claim 14, wherein the identifying of the clusters and the categorizing them into having a high or low density of populated pixels is done in a single step.
  16. 16. The method of any one of claims 13 to 15, wherein the kernel is an edge preserving filter.
  17. 17. The method of any one of claims 13 to 16, wherein the size and/or shape of the kernel is adjusted to improve the generated image.
  18. 18. The method of any one of claims 13 to 17, wherein the size and/or shape of the kernel is about the size of a high density cluster.
  19. 19. The method of any one of claims 13 to 18, wherein the size and/or shape of the kernel is adjusted to suit the peak energy of the gamma rays being used in the medical imaging.
  20. 20. The method of any one of claims 13 to 19, wherein the size and/or shape of the kernel is adjusted to suit the peak energy of the gamma rays being used in the medical imaging, and wherein the peak energy of the gamma rays results from gamma rays emitted from Tc-99m, 1-123, 1-131, Lu-177, In-111, 201-TI, Y-90, Sc-47, Ga-67, Cr-51, Sn-177m, Cu-67, Tm-167, Ru-97, Re-188, Au-199, Pb-203, Ce-141, Co-57, F-18, Ga-68, C-ll, 0-15, N-13, Zr-89, Rb-82, Cu-64, Cd-109, Cs-131, 1-125, Am-241, Cd-109, Ag-109m, U-235, Pb-212, Re-186 and Ho-166.

Description

Density Cluster Imaging Field of the invention This invention relates to density cluster imaging. In particular, though not exclusively, the invention relates to density cluster imaging using gamma rays in medical imaging, as well as methods of using the same. Background of the invention A gamma camera (also called y-camera or scintillation camera) is a device used in medical imaging to image gamma radiation being emitted from radioisotopes. As such, the device must be suitable for the detection of low levels of gamma radiation given off by radioisotopes at doses administered to a subject, while also providing images with suitable resolution to allow a medical practitioner to perform medical analysis, diagnosis or treatment etc. Therefore, gamma ray medical imaging devices have a sensitivity and resolution that are tailored to their role. Typically, the device is required to form medical images of radioisotopes with a gamma emission energy between about 35 keV and about 511 keV, and where these are administered to a subject (e.g. typical body weight of about 70 kg) at levels between about 10 MBq and 1000 MBq. Ideally the images produced will have a clinically meaningful resolution acquired within about 30 minutes or less. The isotope, activity etc. will be adjusted to take account of the conditions e.g. the mass of the subject and the tissue being targeted. Gamma cameras are commonly used to create images in a technique known as scintigraphy. In scintigraphy radioisotopes are commonly attached to tracer agents or drugs (radiopharmaceuticals) which travel to specific organs or tissues, and in that way those target tissues can be imaged. So, this technique can create visual representations of the physiological processes of the target tissues for clinical analysis and medical intervention, as well as visual representation of the function of organs or tissues. Therefore, this technique goes beyond revealing internal structures hidden by the exterior of the subject, it can target certain organs or disease states and/or provide more information about their anatomy and function. Gamma cameras are typically large, expensive and fixed installations, and so are typically housed in a dedicated room in a hospital. Patients are typically required to go to the location and are inserted into the body of the device to be scanned. Smaller gamma cameras with a more limited field of view are more mobile but remain relatively large and unwieldy, and further may be lacking in sensitivity and/or resolution and/or suitable field of view. Examples of gamma cameras used for medical scintigraphy include Siemens Healthineers' Symbia Intevo Excel, Oncovision's Sentinella and Digirad's Ergo Imaging System. A significant problem encountered using gamma ray cameras in medical imaging is making sure that the gamma ray camera substantially only records gamma ray photons that have come directly from the radioisotope that has been given to the subject. Gamma ray photons that have been deflected from their original path (scattered) should not contribute to the image. An ideal scenario is shown schematically in Figure 1. Figure 1 shows a gamma ray photon emanating from a subject (10) that has been dosed with a gamma ray (y) source (11) (shown as the dashed region in the subject). The gamma ray photon (12) passes through a collimator (e.g. a 'pinhole'), hits the detector and is detected by the detector. In this case the detector converts the gamma ray photon into a voltage (23), where the voltage corresponds to the energy of the gamma ray photon. In Figure 1 the output voltage from the device is shown as a voltage peak. However, scattered gamma ray photons (e.g. gamma ray photons emanating from the subject, but where the original trajectory of the gamma ray photon has been changed in some way) and background gamma ray photons can contribute unwanted noise, making the desired image worse. An example of this is shown schematically in Figure 2 where a gamma ray photon is scattered (see the inflection point shown in the dashed line (13)) in an effect known as Compton scattering. In this process the gamma photon encounters and interacts with a charged particle, normally an electron. The gamma photon transfers some of its energy to the charged particle and changes its direction of travel. The gamma ray photon may be from a background source, or indeed originally scattered from the radiation source. Again, the detector converts the scattered gamma ray photon into a voltage. However, in this case, because the scattered gamma ray photon has a lower energy, the detector produces a lower resultant output voltage (24). So, in Figure 2 the scattered gamma ray photon gives a voltage corresponding to the lower (striped) voltage peak (24), whereas a gamma ray photon coming directly from the radiation source corresponds to the bigger (unstriped), voltage peak (23). A gamma ray photon may undergo multiple scattering events, losing energy and changing trajector