System for detecting bone cancer metastases
AssigneeEXINI Diagnostics AB
InventorsIman Hamadeh, Pierre Nordblom, Karl Sjöstrand
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Abstract
The invention relates to a detection system for automatic detection of bone cancer metastases from a set of isotope bone scan images of a patients skeleton, the system comprising a shape identifier unit, a hotspot detection unit, a hotspot feature extraction unit, a first artificial neural network unit, a patient feature extraction unit, and a second artificial neural network unit.
Claims16
A detection system for automatic detection of bone cancer metastases from a set of isotope bone scan images of a patients skeleton, the system comprising:
- a shape identifier unit for identifying anatomical structures of the skeleton pictured in the set of bone scan images, forming an annotated set of images;
- a hotspot detection unit for detecting areas of high intensity in the annotated set of images based on information from the shape identifier regarding the anatomical structures corresponding to different portions of the skeleton of the images;
- a hotspot feature extraction unit for extracting a set of hotspot features for each hot spot detected by the hotspot detection unit;
- a first artificial neural network unit arranged to calculate a likelihood for each hot spot of the hotspot set being a metastasis based on the set of hotspot features extracted by the hotspot feature extraction unit;
- a patient feature extraction unit arranged to extract a set of patient features based on the hotspots detected by the hotspot detection unit and on the likelihood outputs from the first artificial neural network unit;
- and
- a second artificial neural network unit arranged to calculate a likelihood that the patient has one or more cancer metastases, based on the set of patient features extracted by the patient feature extraction unit.
A method for automatically detecting bone cancer metastases from an isotope bone scan image set of a patient, the method comprising the following steps:
- identifying anatomical structures of the skeleton pictured in the set of bone scan images, forming an annotated set of images;
- detecting areas of high intensity in the annotated set of images based on information regarding the anatomical structures corresponding to different portions of the skeleton of the images;
- extracting a set of hotspot features for each hot spot detected;
- feeding, to a first artificial neural network unit arranged to calculate a likelihood for each hot spot of the hotspot set being a metastasis, the set of hotspot features extracted;
- extracting a set of patient features based on the hotspots detected and on the likelihood outputs from the first artificial neural network unit;
- and
- feeding, to a second artificial neural network unit arranged to calculate a likelihood that the patient has one or more cancer metastases, the set of patient features extracted.
Dependencies are inferred from the claim text.