Abstract: Methods, apparatuses, and computer program products are provided for identifying a region of interest within a mammogram image. A method may include applying a clustering algorithm to a histogram of the mammogram image to identify a predefined number of threshold values. The method may further include determining a predefined number of seed values based at least in part on the identified threshold values. The method may additionally include generating a kernel image for each of the seed values. The method may also include using the generated kernel images to identify a region of interest including a breast within the mammogram image. Corresponding apparatuses and computer program products are also provided.

Abstract: Methods, apparatuses, and computer program products are provided for identifying a region of interest within a mammogram image. A method may include applying a clustering algorithm to a histogram of the mammogram image to identify a predefined number of threshold values. The method may further include determining a predefined number of seed values based at least in part on the identified threshold values. The method may additionally include generating a kernel image for each of the seed values. The method may also include using the generated kernel images to identify a region of interest including a breast within the mammogram image. Corresponding apparatuses and computer program products are also provided.

Abstract: Methods, apparatuses, and computer program products are provided for identifying a region of interest within a mammogram image. A method may include applying a clustering algorithm to a histogram of the mammogram image to identify a predefined number of threshold values. The method may further include determining a predefined number of seed values based at least in part on the identified threshold values. The method may additionally include generating a kernel image for each of the seed values. The method may also include using the generated kernel images to identify a region of interest including a breast within the mammogram image. Corresponding apparatuses and computer program products are also provided.

Abstract: 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.

Abstract: 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.

Abstract: Methods, apparatuses, and computer program products are provided for identifying a region of interest within a mammogram image. A method may include applying a clustering algorithm to a histogram of the mammogram image to identify a predefined number of threshold values. The method may further include determining a predefined number of seed values based at least in part on the identified threshold values. The method may additionally include generating a kernel image for each of the seed values. The method may also include using the generated kernel images to identify a region of interest including a breast within the mammogram image. Corresponding apparatuses and computer program products are also provided.