Methods, apparatuses, and computer program products for controlling luminance of non-tissue objects within an image
View Patent ↗Methods, apparatuses, and computer program products are provided for controlling luminance of non-tissue objects within an image. A method may include determining one or more seed pixel values for an image. The method may further include determining, based at least in part on the one or more seed pixel values, one or more regions of the image that include non-tissue objects. The method may additionally include defining a mask comprising the determined one or more regions of the image. The method may also include calculating a mask pixel value based at least in part on a defined luminance value. The method may further include setting pixel values within the mask to the calculated mask pixel value. The method may additionally include causing masking of the image with the mask. Corresponding apparatuses and computer program products are also provided.
1. A method for controlling luminance of non-tissue objects within a medical image, the method comprising:
determining one or more seed pixel values for an image;
determining, based at least in part on the one or more seed pixel values, one or more regions of the image that comprise a non-tissue object;
defining a mask comprising the determined one or more regions of the image that comprise a non-tissue object;
calculating, by a processor, a mask pixel value based at least in part on a defined luminance value;
setting pixel values within the mask to the calculated mask pixel value; and
causing masking of the image with the mask.
2. The method of claim 1 , further comprising:
segmenting the image into a plurality of regions; and
wherein determining one or more regions of the image that comprise a non-tissue object comprises determining one or more of the regions of the segmented image that comprise a non-tissue object.
3. The method of claim 1 , wherein determining one or more seed pixel values comprises determining one or more user-selected pixels, the one or more user-selected pixels being labeled as either mask pixels or non-mask pixels.
4. The method of claim 3 , wherein:
determining one or more regions of the image that comprise a non-tissue object comprises applying a labeling algorithm to propagate the one or more seed pixel labels to one or more segmented regions of the image, resulting in one or more labeled regions of the image; and
defining the mask comprises defining the mask based at least in part on the one or more labeled regions of the image.
5. The method of claim 1 , further comprising:
analyzing a histogram of the image; and
wherein determining one or more seed pixel values comprises determining a seed pixel value representing non-tissue objects based at least in part on a photometric interpretation of the image and on the analysis of the histogram.
6. The method of claim 5 , wherein:
determining one or more regions of the image that comprise a non-tissue object comprises determining one or more regions of the image having an average pixel value satisfying a relationship criterion with respect to the seed pixel value determined to represent non-tissue objects; and
defining the mask comprises defining the mask based at least in part on the one or more regions of the image determined to have an average pixel value satisfying a relationship criterion with respect to the seed pixel value determined to represent non-tissue objects.
7. The method of claim 1 , wherein calculating the mask pixel value comprises calculating the mask pixel value based at least in part on a Digital Imaging and Communications in Medicine (DICOM) Gray Scale Display Function (GSDF).
8. The method of claim 1 , wherein calculating the mask pixel value comprises:
calculating an index value as a function of the defined luminance value; and
calculating the mask pixel value as a function of the calculated index value, a minimum luminance value of a monitor, and a maximum luminance value of the monitor.
9. The method of claim 8 , wherein:
calculating the index value comprises calculating an index value, j(L), as a function of the defined luminance value, L, in accordance with
j
(
L
)
=
A
+
B
·
Log
10
(
L
)
+
C
·
(
Log
10
(
L
)
)
2
+
D
·
(
Log
10
(
L
)
)
3
+
E
·
(
Log
10
(
L
)
)
4
+
F
·
(
Log
10
(
L
)
)
5
+
G
·
(
Log
10
(
L
)
)
6
+
H
·
(
Log
10
(
L
)
)
7
+
I
·
(
Log
10
(
L
)
)
8
,
wherein Log 10 represents logarithm to the base 10, and A=71.498068, B=94.593053, C=41.912053, D=9.8247004, E=0.28175407, F=−1.1878455, G=−0.18014349, H=0.14710899, I=−0.017046845;
in an instance in which the image is unsigned, calculating the mask pixel value comprises calculating a mask pixel value, X, as function of the calculated index value, a minimum luminance value of a monitor, j min , and a maximum luminance value of the monitor, j max , in accordance with
X
=
j
(
L
)
-
j
min
j
max
-
j
min
(
2
″
-
1
)
,
wherein n is a number of bits stored for each pixel value; and
in an instance in which the image is signed, calculating the mask pixel value comprises calculating a mask pixel value, X, as function of the calculated index value, a minimum luminance value of a monitor, j min , and a maximum luminance value of the monitor, j max , in accordance with
X
=
j
(
L
)
-
j
min
j
max
-
j
min
(
2
″
-
1
)
-
2
n
-
1
,
wherein n is a number of bits stored indicated by a header of the image.
10. The method of claim 1 , wherein the image comprises a mammogram image.
11. An apparatus for controlling luminance of non-tissue objects within a medical image, the apparatus comprising at least one processor, wherein the at least one processor is configured to cause the apparatus to at least:
determine one or more seed pixel values for an image;
determine, based at least in part on the one or more seed pixel values, one or more regions of the image that comprise a non-tissue object;
define a mask comprising the determined one or more regions of the image that comprise a non-tissue object;
calculate a mask pixel value based at least in part on a defined luminance value;
set pixel values within the mask to the calculated mask pixel value; and
cause masking of the image with the mask.
12. The apparatus of claim 11 , wherein the at least one processor is configured to further cause the apparatus to:
segment the image into a plurality of regions; and
determine one or more regions of the image that comprise a non-tissue object at least in part by determining one or more of the regions of the segmented image that comprise a non-tissue object.
13. The apparatus of claim 11 , wherein the at least one processor is configured to cause the apparatus to determine one or more seed pixel values at least in part by determining one or more user-selected pixels, the one or more user-selected pixels being labeled as either mask pixels or non-mask pixels.
14. The apparatus of claim 13 , wherein the at least one processor is configured to cause the apparatus to:
determine one or more regions of the image that comprise a non-tissue object at least in part by applying a labeling algorithm to propagate the one or more seed pixel labels to one or more segmented regions of the image, resulting in one or more labeled regions of the image; and
define the mask at least in part by defining the mask based at least in part on the one or more labeled regions of the image.
15. The apparatus of claim 11 , wherein the at least one processor is configured to further cause the apparatus to
analyze a histogram of the image; and
determine one or more seed pixel values at least in part by determining a seed pixel value representing non-tissue objects based at least in part on a photometric interpretation of the image and on the analysis of the histogram.
16. The apparatus of claim 15 , wherein the at least one processor is configured to cause the apparatus to:
determine one or more regions of the image that comprise a non-tissue object at least in part by determining one or more regions of the image having an average pixel value satisfying a relationship criterion with respect to the seed pixel value determined to represent non-tissue objects; and
define the mask at least in part by defining the mask based at least in part on the one or more regions of the image determined to have an average pixel value satisfying a relationship criterion with respect to the seed pixel value determined to represent non-tissue objects.
17. The apparatus of claim 11 , wherein the at least one processor is configured to cause the apparatus to calculate the mask pixel value at least in part by calculating the mask pixel value based at least in part on a Digital Imaging and Communications in Medicine (DICOM) Gray Scale Display Function (GSDF).
18. The apparatus of claim 11 , wherein the at least one processor is configured to cause the apparatus to calculate the mask pixel value at least in part by:
calculating an index value as a function of the defined luminance value; and
calculating the mask pixel value as a function of the calculated index value, a minimum luminance value of a monitor, and a maximum luminance value of the monitor.
19. The apparatus of claim 18 , wherein the at least one processor is further configured to cause the apparatus to:
calculate the index value at least in part by calculating an index value, j(L), as a function of the defined luminance value, L, in accordance with
j
(
L
)
=
A
+
B
·
Log
10
(
L
)
+
C
·
(
Log
10
(
L
)
)
2
+
D
·
(
Log
10
(
L
)
)
3
+
E
·
(
Log
10
(
L
)
)
4
+
F
·
(
Log
10
(
L
)
)
5
+
G
·
(
Log
10
(
L
)
)
6
+
H
·
(
Log
10
(
L
)
)
7
+
I
·
(
Log
10
(
L
)
)
8
,
wherein Log 10 represents logarithm to the base 10, and A=71.498068, B=94.593053, C=41.912053, D=9.8247004, E=0.28175407, F=−1.1878455, G=−0.18014349, H=0.14710899, I=−0.017046845;
in an instance in which the image is unsigned, calculate the mask pixel value at least in part by calculating a mask pixel value, X, as function of the calculated index value, a minimum luminance value of a monitor, j min , and a maximum luminance value of the monitor, j max , in accordance with
X
=
j
(
L
)
-
j
min
j
max
-
j
min
(
2
″
-
1
)
,
wherein n is a number of bits stored indicated by a header of the image; and
in an instance in which the image is signed, calculate the mask pixel value at least in part by calculating a mask pixel value, X, as function of the calculated index value, a minimum luminance value of a monitor, j min , and a maximum luminance value of the monitor, j max , in accordance with
X
=
j
(
L
)
-
j
min
j
max
-
j
min
(
2
″
-
1
)
-
2
n
-
1
,
wherein n is a number of bits stored for each pixel value.
20. The apparatus of claim 11 , further comprising at least one memory storing instructions that when executed by the at least one processor cause the apparatus to:
determine one or more seed pixel values for the image;
determine, based at least in part on the one or more seed pixel values, one or more regions of the image that comprise a non-tissue object;
define the mask;
calculate the mask pixel value;
set pixel values within the mask to the calculated mask pixel value; and
cause masking of the image with the mask.
21. A computer program product for controlling luminance of non-tissue objects within a medical image, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program instructions stored therein, the computer-readable program instructions comprising:
program instructions configured to determine one or more seed pixel values for an image;
program instructions configured to determine, based at least in part on the one or more seed pixel values, one or more regions of the image that comprise a non-tissue object;
program instructions configured to define a mask comprising the determined one or more regions of the image that comprise a non-tissue object;
program instructions configured to calculate a mask pixel value based at least in part on a defined luminance value;
program instructions configured to set pixel values within the mask to the calculated mask pixel value; and
program instructions configured to cause masking of the image with the mask.