Logistic model to determine 3D z-wise lesion connectivity
AssigneeInternational Business Machines Corporation
InventorsYi-Qing Wang, Giovanni John Jacques Palma
Life of this patent
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Abstract
A mechanism is provided to implement a trained machine learning computer model for determining z-wise lesion connectivity. The mechanism identifies, for a given slice in a three-dimensional medical image, a first lesion in the given slice and a second lesion in an adjacent slice in the three-dimensional medical image. The mechanism determines a first intersect value between the first lesion and the second lesion with respect to the first lesion and determines a second intersect value between the first lesion and the second lesion with respect to the second lesion. The mechanism determines whether the first lesion and the second lesion belong to the same three-dimensional lesion based on the first and second intersect values.
Claims20
A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory storing instructions executed by the at least one processor to implement a trained machine learning computer model for determining z-wise lesion connectivity, the method comprising:
- identifying, for a given slice in a three-dimensional medical image, a first lesion in the given slice and a second lesion in an adjacent slice in the three-dimensional medical image;
- determining a first intersect value between the first lesion and the second lesion with respect to the first lesion;
- determining a second intersect value between the first lesion and the second lesion with respect to the second lesion;
- and
- determining whether the first lesion and the second lesion belong to the same three-dimensional lesion based on the first and second intersect values.
A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a trained machine learning computer model for determining z-wise lesion connectivity, wherein the trained machine learning computer model executes to:
- identify, for a given slice in a three-dimensional medical image, a first lesion in the given slice and a second lesion in an adjacent slice in the three-dimensional medical image;
- determine a first intersect value between the first lesion and the second lesion with respect to the first lesion;
- determine a second intersect value between the first lesion and the second lesion with respect to the second lesion;
- and
- determine whether the first lesion and the second lesion belong to the same three-dimensional lesion based on the first and second intersect values.
An apparatus comprising:
- a processor;
- and
- a memory coupled to the processor, wherein the memory stores instructions which, when executed by the processor, cause the processor to implement a trained machine learning computer model for determining z-wise lesion connectivity, wherein the trained machine learning computer model executes to:
- identify, for a given slice in a three-dimensional medical image, a first lesion in the given slice and a second lesion in an adjacent slice in the three-dimensional medical image;
- determine a first intersect value between the first lesion and the second lesion with respect to the first lesion;
- determine a second intersect value between the first lesion and the second lesion with respect to the second lesion;
- and
- determine whether the first lesion and the second lesion belong to the same three-dimensional lesion based on the first and second intersect values.
Dependencies are inferred from the claim text.