Method for measuring muscle mass
The present invention relates to a method for measuring muscle mass, including: a first selection step, wherein a frame selection information is obtained by using a frame to select a fascia region from a provided computed tomography image under the condition that the window width ranges from 300 HU to 500 HU and the window level ranges from 40 HU to 50 HU, wherein the selected range of the fascia region includes a muscle; and a second selection step, wherein a muscle information of the muscle is obtained by calculating a pixel value in the frame-selected fascia region under the condition that the HU value of the CT image ranges from −29 HU to 150 HU.
1. A method for measuring muscle mass, comprising:
a first selection step, wherein a frame selection information is obtained by using a frame to select a fascia region from a provided computed tomography image under the condition that the window width ranges from 300 HU to 500 HU and the window level ranges from 40 HU to 50 HU, wherein the selected range of the fascia region includes a muscle; and
a second selection step, wherein a muscle information of the muscle is obtained by calculating a pixel value in the frame-selected fascia region under the condition that the HU value of the CT image ranges from −29 HU to 150 HU.
2. The method as claimed in claim 1 , wherein the computed tomography image is selected from a group consisting of a horizontal computed tomography scan of the third vertebra or a horizontal computed tomography scan of fourth vertebra, and wherein the muscle is chosen from a group consisting of the following: transverse abdominis, rectus abdominis, internal oblique, external oblique, psoas, quadratus lumborum, paraspinal muscle and combinations thereof.
3. The method as claimed in claim 1 , further comprising a record step to store the frame selection information in a record module after the first selection step and to store the muscle information in the record module after the second selection step.
4. The method as claimed in claim 3 , further comprising using an analysis module to automatically select the fascia region from the computed tomography image in the first selection step, wherein the analysis module receives a frame selection reference object and then organize and summarize a detail feature within the frame selection range of the frame selection reference object, wherein the analysis module use the detail feature to obtain the frame selection information by framing out a portion of the computed tomography image which having the same detail feature.
5. The method as claimed in claim 4 , further comprising an intelligent calculation step after the record step, wherein a calculation module is used to present the muscle information in the digital format so as to express one of the following of the muscle: mass, density and distribution, wherein the calculation module communicates with the record module to receive the muscle information through signal.
6. A method for measuring muscle mass, comprising:
a first selection step, wherein a first frame selection information and a second frame selection information are obtained by using a frame to select a first fascia region and a second fascia region from a provided computed tomography image under the condition that the window width ranges from 300 HU to 500 HU and the window level ranges from 40 HU to 50 HU, wherein the first selected range of the fascia region includes a first muscle and the second selected range of the fascia region includes a second muscle; and
a second selection step, wherein a first muscle information of the first muscle is obtained by calculating a pixel value in the frame-selected first fascia region and a second muscle information of the first muscle is obtained by calculating a pixel value in the frame-selected second fascia region under the condition that the HU value of the CT image ranges from −29 HU to 150 HU.
7. The method as claimed in claim 6 , wherein the computed tomography image is selected from a group consisting of a horizontal computed tomography scan of the third vertebra or a horizontal computed tomography scan of fourth vertebra, wherein the first muscle is chosen from a group consisting of the following: transverse abdominis, rectus abdominis, internal oblique, external oblique, psoas, quadratus lumborum, paraspinal muscle and combinations thereof, and wherein the second muscle is chosen from a group consisting of the following: transverse abdominis, rectus abdominis, internal oblique, external oblique, psoas, quadratus lumborum, paraspinal muscle and combinations thereof.
8. The method as claimed in claim 6 , further comprising a record step to store the frame selection information in a record module after the first selection step and to store the first muscle information and the second muscle information in the record module after the second selection step.
9. The method as claimed in claim 8 , further comprising using an analysis module to automatically select the first fascia region and the second fascia region from the computed tomography image in the first selection step, wherein the analysis module receives a frame selection reference object and then organize and summarize a detail feature within the frame selection range of the frame selection reference object, wherein the analysis module use the detail feature to obtain the first frame selection information and the second frame selection information by framing out a portion of the computed tomography image which having the same detail feature.
10. The method as claimed in claim 9 , further comprising an intelligent calculation step after the record step, wherein a calculation module is used to present the first muscle information and the second muscle information in the digital format so as to express one of the following the first muscle and the second muscle: mass, density and distribution, wherein the calculation module communicates with the record module to receive the first muscle information and the second muscle information through signal.