Information processing method, medical image diagnostic apparatus, and information processing system
A method of processing information acquired by imaging performed by a medical image diagnostic apparatus, the method including but not limited to at least one of (A) acquiring a training image volume including at least one three-dimensional object having an embedded three-dimensional feature having a first cross-sectional area in a first three-dimensional plane; selecting a second cross-sectional area in a second three-dimensional plane containing the embedded three-dimensional feature, wherein the second cross-sectional area is larger than the first cross-sectional area; and training an untrained neural network with an image of the second cross-sectional area generated from the training image volume; and (B) acquiring a first set of training data; determining a first distribution of tissue density information from the first set of training data; generating from the first set of training data a second set of training data by performing at least one of a tissue-density shifting process and a tissue-density scaling process; and training an untrained neural network with the first and second sets of training data to obtain a trained neural network.
1 . An information processing method for information acquired by imaging performed by a medical image diagnostic apparatus, the information processing method comprising:
acquiring a training image volume including at least one three-dimensional object having an embedded three-dimensional feature having a first cross-sectional area in a first three-dimensional plane;
determining, by rotating the first three-dimensional plane, a second three-dimensional plane different from the first three-dimensional plane, and containing the embedded three-dimensional feature so that a second cross-sectional area of the embedded three-dimensional feature in the second three-dimensional plane is larger than the first cross-sectional area;
generating, from the acquired training image volume, a first image along the first three-dimensional plane and a second image along the second three-dimensional plane; and
training an untrained neural network for each part of a plurality of body parts with the first and second images generated from the acquired training image volume.
2 . The method according to claim 1 , wherein the first three-dimensional plane is orthogonal to the second three-dimensional plane.
3 . The method according to claim 1 , wherein the second three-dimensional plane is determined to provide a maximum cross-sectional area of the embedded three-dimensional feature.
4 . The method according to claim 1 , wherein the embedded three-dimensional feature is a stent.
5 . The method according to claim 1 , wherein the training image volume comprises image data reconstructed from CT projection data.
6 . An apparatus for an information processing method for information acquired by imaging performed by a medical image diagnostic apparatus, comprising:
processing circuitry configured to:
acquire a training image volume including at least one three-dimensional object having an embedded three-dimensional feature having a first cross-sectional area in a first three-dimensional plane;
determine, by rotating the first three-dimensional plane, a second three-dimensional plane different from the first three-dimensional plane, and containing the embedded three-dimensional feature so that a second cross-sectional area of the embedded three-dimensional feature in the second three-dimensional plane is larger than the first cross-sectional area;
generate, from the acquired training image volume, a first image along the first three-dimensional plane and a second image along the second three-dimensional plane; and
train an untrained neural network for each part of a plurality of body parts with the first and second images generated from the acquired training image volume.
7 . The apparatus according to claim 6 , wherein the first three-dimensional plane is orthogonal to the second three-dimensional plane.
8 . The apparatus according to claim 6 , wherein the second three-dimensional plane is determined to provide a maximum cross-sectional area of the embedded three-dimensional feature.
9 . The apparatus according to claim 6 , wherein the embedded three-dimensional feature is a stent.
10 . The apparatus according to claim 6 , wherein the training image volume comprises image data reconstructed from CT projection data.