Method, system and apparatus for rendering medical image data
A method of rendering medical image data includes: obtaining an image, having a plurality of voxels, of a volume of patient tissue having a plurality of tissue types; for each of the plurality of voxels: determining a first type indicator value indicating a likelihood that the voxel depicts a first one of the tissue types; storing the first type indicator value in association with the voxel; setting a first type indicator threshold for the first tissue type; rendering the image on a display and applying a first visual filter to a first subset of the voxels having type indicator values that satisfy the first type indicator threshold; and updating the rendering, responsive to receiving input data specifying a modified first type indicator threshold, to apply the first visual filter to an updated first subset of the voxels having first type indicator values that satisfy the modified first type indicator threshold.
1. A method of rendering medical image data, comprising:
obtaining an image of a volume of patient tissue having a plurality of tissue types; the image comprising a plurality of voxels;
for each of the plurality of voxels:
determining a first type indicator value indicating a likelihood that the voxel depicts a first one of the tissue types; and
storing the first type indicator value in association with the voxel;
setting a first type indicator threshold for the first tissue type;
rendering the image on a display and applying a first visual filter to a first subset of the voxels having type indicator values that satisfy the first type indicator threshold;
rendering, on the display with the image, a selectable threshold adjustment element;
receiving input data via selection of the threshold adjustment element, the input data defining a modified first type indicator threshold; and
updating the rendering, responsive to receiving the input data, to apply the first visual filter to an updated first subset of the voxels having first type indicator values that satisfy the modified first type indicator threshold.
2. The method of claim 1 , further comprising:
for each of the plurality of voxels:
determining a second type indicator value indicating a likelihood that the voxel depicts a second one of the tissue types;
storing the second type indicator value in association with the voxel; and setting a second type indicator threshold for the second tissue type.
3. The method of claim 2 , wherein the rendering further comprises applying a second visual filter to a second subset of the voxels having second type indicators that satisfy the second type indicator threshold.
4. The method of claim 3 , wherein the rendering further comprises:
when a voxel is a member of the first subset and the second subset, determining whether the corresponding first and second type indicator values satisfy the respective type indicator thresholds; and
when the determination is affirmative, selecting one of the first and second visual filters to apply to the voxel.
5. The method of claim 1 , wherein determining the first type indicator value comprises executing a probability model based on the intensity of the voxel and the intensity of adjacent voxels.
6. The method of claim 1 , wherein the first type indicator value is an intensity value of the voxel.
7. The method of claim 1 , wherein the plurality of tissue types includes one or more of vascular tissue and nervous tissue.
8. The method of claim 1 , wherein the plurality of tissue types includes one or more of vascular tissue, grey matter nervous tissue, and white matter nervous tissue.
9. A computing device for rendering medical image data, comprising:
an input device;
a display;
a memory;
a processor interconnected with the input device, the display and the memory, the processor configured to;
obtain, from the memory, an image of a volume of patient tissue having a plurality of tissue types; the image comprising a plurality of voxels;
for each of the plurality of voxels:
determine a first type indicator value indicating a likelihood that the voxel depicts a first one of the tissue types; and
store the first type indicator value in association with the voxel;
set a first type indicator threshold for the first tissue type;
render the image on the display and apply a first visual filter to a first subset of the voxels having type indicator values that satisfy the first type indicator threshold;
render, on the display with the image, a selectable threshold adjustment element;
receive input data via selection of the threshold adjustment element at the input the device, the input data defining a modified first type indicator threshold; and
update the rendering, responsive to receiving input data via the input device specifying a modified first type indicator threshold, to apply the first visual filter to an updated first subset of the voxels having first type indicator values that satisfy the modified first type indicator threshold.
10. The computing device of claim 9 , the processor further configured to:
for each of the plurality of voxels:
determine a second type indicator value indicating a likelihood that the voxel depicts a second one of the tissue types;
store the second type indicator value in association with the voxel; and
set a second type indicator threshold for the second tissue type.
11. The computing device of claim 10 , the processor further configured to render the image by: applying a second visual filter to a second subset of the voxels having second type indicators that satisfy the second type indicator threshold.
12. The computing device of claim 11 , the processor further configured to render the image by:
when a voxel is a member of the first subset and the second subset, determining whether the corresponding first and second type indicator values satisfy the respective type indicator thresholds; and
when the determination is affirmative, selecting one of the first and second visual filters to apply to the voxel.
13. The computing device of claim 9 , the processor further configured to determine the first type indicator value by executing a probability model based on the intensity of the voxel and the intensity of adjacent voxels.
14. The computing device of claim 9 , wherein the first type indicator value is an intensity value of the voxel.
15. The computing device of claim 9 , wherein the plurality of tissue types includes one or more of vascular tissue and nervous tissue.
16. The computing device of claim 9 , wherein the plurality of tissue types includes one or more of vascular tissue, grey matter nervous tissue, and white matter nervous tissue.