US 11,937,962 B2
Systems and methods for automated and interactive analysis of bone scan images for detection of metastases
Karl Vilhelm Sjöstrand, Atlantic Highlands, NJ (US); Jens Filip Andreas Richter, Lund (SE); and Lars Edenbrandt, Lund (SE)
Assigned to Progenics Pharmaceuticals, Inc., N. Billerica, MA (US); and EXINI Diagnostics AB, Lund (SE)
Filed by Progenics Pharmaceuticals, Inc., N. Billerica, MA (US); and EXINI Diagnostics AB, Lund (SE)
Filed on Nov. 18, 2022, as Appl. No. 17/989,863.
Application 17/989,863 is a continuation of application No. 16/856,120, filed on Apr. 23, 2020, granted, now 11,534,125.
Claims priority of provisional application 62/837,955, filed on Apr. 24, 2019.
Prior Publication US 2023/0148980 A1, May 18, 2023
Int. Cl. G06K 9/00 (2022.01); A61B 6/00 (2006.01); A61B 6/03 (2006.01); A61K 51/04 (2006.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); G16H 70/60 (2018.01)
CPC A61B 6/469 (2013.01) [A61B 6/037 (2013.01); A61B 6/465 (2013.01); A61B 6/505 (2013.01); A61B 6/5217 (2013.01); A61B 6/5258 (2013.01); A61B 6/563 (2013.01); A61K 51/0489 (2013.01); G06T 7/0012 (2013.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); G16H 70/60 (2018.01); G06T 2200/24 (2013.01); G06T 2207/30008 (2013.01); G06T 2207/30096 (2013.01)] 30 Claims
OG exemplary drawing
 
1. A method for lesion marking and quantitative analysis of nuclear medicine images of a human subject, the method comprising:
(a) accessing, by a processor of a computing device, a bone scan image set for the human subject, said bone scan image set obtained following administration of an agent to the human subject;
(b) automatically segmenting, by the processor, each image in the bone scan image set to identify one or more skeletal regions of interest, each corresponding to a particular anatomical region of a skeleton of the human subject, thereby obtaining an annotated set of images, wherein the one or more skeletal regions of interest comprise at least one of (i) and (ii):
(i) a femur region corresponding to a portion of a femur of the human subject; and
(ii) a humerus region corresponding to a portion of a humerus of the human subject;
(c) automatically detecting, by the processor, an initial set of one or more hotspots, each hotspot corresponding to an area of elevated intensity in the annotated set of images, said automatically detecting comprising identifying the one or more hotspots using intensities of pixels in the annotated set of images and using one or more region-dependent threshold values, and wherein the one or more region dependent threshold values include one or more values associated with the femur region and/or the humerus region that provide enhanced hotspot detection sensitivity in the femur region and/or the humerus region to compensate for reduced uptake of the agent therein;
(d) for each hotspot in the initial set of hotspots, extracting, by the processor, a set of hotspot features associated with the hotspot;
(e) for each hotspot in the initial set of hotspots, calculating, by the processor, a metastasis likelihood value corresponding to a likelihood of the hotspot representing a metastasis, based on the set of hotspot features associated with the hotspot; and
(f) causing, by the processor, rendering of a graphical representation of at least a portion of the initial set of hotspots for display within a graphical user interface (GUI),
wherein the one or more region dependent threshold values comprise (i) a first, reduced intensity, threshold value associated with the femur region and/or the humerus region and (ii) a second threshold value associated with one or more other skeletal regions of interest, wherein the first threshold value is lower than the second threshold value, thereby increasing detection sensitivity in the femur region and/or the humerus region.