US-12622656-B2 - Methods and apparatus for medical imaging event detection and image reconstruction

Abstract

Systems and methods for detecting multiple events during nuclear imaging scans, and for reconstructing images based on the detected events, are disclosed. In some embodiments, an image scanning system scans a subject, and generates a signal characterizing a detection event. The system applies a peak detection process to the signal and, based on the application of the peak detection process, detects a position of each of a plurality of peaks of the signal. Further, the system determines an amplitude of each of the peaks of the signal. The system also determines an energy value for each of the peaks based on applying a curve fitting process to the position and the amplitude of each of the peaks. The system may also determine a time-offset value for a peak based on its position in relation to a previous peak, and may transmit the energy values and corresponding times to generate time-coincident pairs for image reconstruction.

Inventors

• Ziad Burbar
• STEFAN SIEGEL

Assignees

• SIEMENS MEDICAL SOLUTIONS USA, INC.

Dates

Publication Date

20260512

Application Date

20240325

Claims (20)

1. 1 . A computer-implemented method comprising: receiving at least one signal characterizing a detection event; applying a peak detection process to the at least one signal and, based on the application of the peak detection process, detecting a position of each of at least two peaks of the at least one signal; determining an amplitude of each of the at least two peaks of the at least one signal; applying a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve fitting process, determining an energy value for each of the at least two peaks; and transmitting the energy value for each of the at least two peaks.
2. 2 . The computer-implemented method of claim 1 , wherein applying the curve fitting process comprises: inputting the position and the amplitude of a first peak of the at least two peaks to an executed curve fitting model; receiving parameter values from the executed curve fitting model; and determining the energy value for the first peak based on the parameter values.
3. 3 . The computer-implemented method of claim 2 , wherein the executed curve fitting model is based on a least squares means algorithm.
4. 4 . The computer-implemented method of claim 2 , wherein applying the curve fitting process comprises: inputting the position and the amplitude of a second peak of the at least two peaks to the executed curve fitting model; receiving additional parameter values from the executed curve fitting model; and determining the energy value for the second peak based on the additional parameter values.
5. 5 . The computer-implemented method of claim 1 , wherein the at least two peaks consists of two peaks.
6. 6 . The computer-implemented method of claim 1 , further comprising generating a time for each of the at least two peaks based on the respective position of each of the at least two peaks.
7. 7 . The computer-implemented method of claim 6 , wherein generating the time for each of the at least two peaks: generating a first time for a first of the at least two peaks based on sampling a system time; determining an offset value between the at least two peaks based on the position of each of the at least two peaks; and generating a second time for a second of the at least two peaks based on the first time and the offset value.
8. 8 . The computer-implemented method of claim 1 , further comprising receiving the at least one signal from a scanner of an image scanning system.
9. 9 . The computer-implemented method of claim 1 , wherein the at least one signal comprises a first signal that characterizes energy levels of the detection event.
10. 10 . The computer-implemented method of claim 9 , wherein the at least one signal comprises a second signal that characterizes a first dimension location of a crystal that detected the detection event.
11. 11 . The computer-implemented method of claim 10 , wherein the at least one signal comprises a third signal that characterizes a second dimension location of the crystal that detected the detection event.
12. 12 . The computer-implemented method of claim 1 , further comprising generating image measurement data based on the energy value for each of the at least two peaks.
13. 13 . The computer-implemented method of claim 12 , wherein the image measurement data is positron emission tomography (PET) measurement data.
14. 14 . The computer-implemented method of claim 1 , wherein applying the curve fitting process comprises: generating output data characterizing at least two pulses; determining an area under each of the at least two pulses; and determining the energy value for each of the at least two peaks based on the respective area.
15. 15 . A non-transitory computer readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising: receiving at least one signal characterizing a detection event; applying a peak detection process to the at least one signal and, based on the application of the peak detection process, detecting a position of each of at least two peaks of the at least one signal; determining an amplitude of each of the at least two peaks of the at least one signal; applying a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve fitting process, determining an energy value for each of the at least two peaks; and transmitting the energy value for each of the at least two peaks.
16. 16 . The non-transitory computer readable medium of claim 15 wherein the instructions, when executed by the at least one processor, further cause the at least one processor to perform operations comprising: inputting the position and the amplitude of a first peak of the at least two peaks to an executed curve fitting model; receiving parameter values from the executed curve fitting model; and determining the energy value for the first peak based on the parameter values.
17. 17 . The non-transitory computer readable medium of claim 15 , wherein the instructions, when executed by the at least one processor, further cause the at least one processor to perform operations comprising generating a time for each of the at least two peaks based on the respective position of each of the at least two peaks.
18. 18 . The non-transitory computer readable medium of claim 17 , wherein the instructions, when executed by the at least one processor, further cause the at least one processor to perform operations comprising: generating a first time for a first of the at least two peaks based on sampling a system time; determining an offset value between the at least two peaks based on the position of each of the at least two peaks; and generating a second time for a second of the at least two peaks based on the first time and the offset value.
19. 19 . A system comprising: a memory device storing instructions; a transceiver; and at least one processor communicatively coupled to the transceiver and to the memory device, the at least one processor configured to execute the instructions to: receive, via the transceiver, at least one signal characterizing a detection event; apply a peak detection process to the at least one signal and, based on the application of the peak detection process, detect a position of each of at least two peaks of the at least one signal; determine an amplitude of each of the at least two peaks of the at least one signal; apply a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve fitting process, determine an energy value for each of the at least two peaks; and transmit, via the transceiver, the energy value for each of the at least two peaks.
20. 20 . The system of claim 19 , wherein the at least one processor is configured to execute the instructions to: input the position and the amplitude of a first peak of the at least two peaks to an executed curve fitting model; receive parameter values from the executed curve fitting model; and determine the energy value for the first peak based on the parameter values.

Description

FIELD Aspects of the present disclosure relate in general to medical diagnostic systems and, more particularly, to capturing and reconstructing images from nuclear imaging systems for diagnostic and reporting purposes. BACKGROUND Nuclear imaging systems can employ various technologies to capture images. For example, some nuclear imaging systems employ positron emission tomography (PET) to capture images. PET is a nuclear medicine imaging technique that produces tomographic images representing the distribution of positron emitting isotopes within a body. Some nuclear imaging systems combine images from PET and a co-modality, such as computed tomography (CT) or Magnetic Resonance Imaging (MRI). CT is an imaging technique that uses x-rays to produce anatomical images. Magnetic Resonance Imaging (MRI) is an imaging technique that uses magnetic fields and radio waves to generate anatomical and functional images, and may also be used as a co-modality. These nuclear imaging systems can combine images from PET and co-modality scanners during an image fusion process to produce images that show information from both the PET scan and the co-modality scan (e.g., PET/CT systems). Moreover, the nuclear imaging systems may generate an attenuation map that can be used to correct the PET measurement data during image reconstruction. Typically, PET systems (e.g., time-of-flight (TOF) PET systems) include a scanner with detector elements that include crystals which can detect gamma rays during the scanning process. The detector elements include crystals that detect the gamma rays. The systems can generate measurement data characterizing an image based on these detections. Sometimes, however, these systems ignore or miss detection events when, for instance, multiple detection events occur near each other in time. As a result, the generated measurement data may suffer in accuracy, as well as any medical image reconstructed based on the measurement data. As such, there are opportunities to address these and other deficiencies in nuclear imaging systems. SUMMARY Systems and methods for detecting multiple events during nuclear imaging scans, and for reconstructing medical images based on the detected events, are disclosed. In some embodiments, a computer-implemented method includes receiving at least one signal characterizing a detection event. The method also includes applying a peak detection process to the at least one signal and, based on the application of the peak detection process, detecting a position of each of at least two peaks of the at least one signal. Further, the method includes determining an amplitude of each of the at least two peaks of the at least one signal. The method also includes applying a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve fitting process, determining an energy value for each of the at least two peaks. The method further includes transmitting the energy value for each of the at least two peaks. In some embodiments, a non-transitory computer readable medium stores instructions that, when executed by at least one processor, cause the at least one processor to perform operations including receiving at least one signal characterizing a detection event. The operations also include applying a peak detection process to the at least one signal and, based on the application of the peak detection process, detecting a position of each of at least two peaks of the at least one signal. Further, the operations include determining an amplitude of each of the at least two peaks of the at least one signal. The operations also include applying a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve fitting process, determining an energy value for each of the at least two peaks. The operations further include transmitting the energy value for each of the at least two peaks In some embodiments, a system includes a memory device storing instructions, a transceiver, and at least one processor communicatively coupled the transceiver and the memory device. The at least one processor is configured to execute the instructions to receive, via the transceiver, at least one signal characterizing a detection event. The at least one processor is also configured to execute the instructions to apply a peak detection process to the at least one signal and, based on the application of the peak detection process, detect a position of each of at least two peaks of the at least one signal. Further, the at least one processor is configured to execute the instructions to determine an amplitude of each of the at least two peaks of the at least one signal. The at least one processor is also configured to execute the instructions to apply a curve fitting process to the position and the amplitude of each of the at least two peaks and, based on the application of the curve f