The invention relates to a method of image segmentation comprising the step of accessing a prior model representative of a structure conceived to be segmented in an image.
The invention further relates to a system for image segmentation comprising an input for accessing a prior model representative of a structure conceived to be segmented in an image.
The invention still further relates to a computer program for enabling an image segmentation, said computer program comprising instructions causing a processor to carry out the step of accessing a prior model representative of a structure conceived to be segmented in an image.
An embodiment of the method as set forth in the opening paragraph is known from WO 2005/008587 A1. The known method is arranged to segment an image, notably a medical diagnostic image, using a model-based segmentation method, whereby organ models are represented by flexible surfaces and are adapted to boundaries of the object of interest. For this purpose the known method is further arranged to use organ-specific data, such as shape properties of an organ or organ boundary characteristics, such as a gradient, a gradient direction and an intensity range, or tissue properties of the organ. The shape model is then used in its unaltered form and is being deformed by a suitable image segmentation algorithm whereby organ-specific data are used to adapt said model to object boundaries.
It is a disadvantage of the known method that it uses an a-priori constructed prior model, notably a shape model, which is built based on a number of example images and corresponding results of their respective image segmentations. For medical applications, since these example segmentations are difficult to collect, they typically represent the normal subject population images. Moreover, the a-priori constructed shape model cannot comprise a variety of shapes and sizes of the human population and cannot represent most pathologies. Both shortcomings lead to inferior segmentation results, in particular, for atypical images.
It is an object of the invention to provide a method for image segmentation which is robust for a substantially wide range of subjects. To this end the method according to the invention comprises the following steps:
The technical measure of the invention is based on the insight that by providing the supplementary information the prior model can easily be changed meeting the requirements of a current case. It is noted that the prior model may comprise a shape model, an organ size model, representing physical dimensions of an organ, a motion model, an image contrast and/or appearance model, etc. In terms of the invention, it is understood that the term ‘changing’ refers either to amending/adjusting the accessed prior model or to diverting to a different prior model. The latter possibility is advantageous when segmenting medical data showing an abnormality, like pathology in anatomical data.
In an embodiment of the method according to the invention the supplementary information is retrieved from the image data.
Preferably, for medical images stored in a DICOM (Digital Communication in Medicine) format, supplementary information, such as the age of a patient, gender, body size, etc. can be automatically retrieved in an electronic form. The invention is not limited to operating with DICOM images, other possibilities of digital data extraction comprise Picture Arching and Communication (PACS), Hospital Information Systems (HIS) and/or Radiology Information Systems (RIS) sources, or any other electronic formats enabling access to supplementary information next to image data. The technical measure of the invention ensures an increased level of automation during data processing. Alternatively, the supplementary information can be provided by a human operator in an interactive way, for example using a suitable user interface. This supplementary information is used to adapt the expected size and/or expected shape of an anatomical structure conceived to be segmented, for example by scaling the overall size of the prior model. Alternatively, a different prior model from a pre-stored set of available models can be selected in lieu of the accessed prior model, for example a suitable model representing a pathology expected or diagnosed in a patient. Still alternatively, the prior model can be substituted by another model representative of a population group the patient belongs to.
In a further embodiment of the method according to the invention, the method further comprises the step of performing an image segmentation using the further model.
According to this technical measure a robust image segmentation method is enabled, which provides reliable segmentation results for a great variety of population groups, is age-specific and is capable of coping with atypical shapes representative of pathologies.
In the system according to the invention the input is further arranged for accessing supplementary information, the system further comprising a processor unit for changing the prior model using the supplementary information yielding a further model. Further advantageous embodiments of the system according to the invention are given in claims 7 and 8. The system according to the invention will be described in more detail with reference to
The computer program according to the invention for enabling image segmentation comprises further instructions causing a processor to carry out the following steps:
Further advantageous embodiments of the computer program according to the invention are given in claims 10 and 11. The computer program according to the invention provides means for enabling automatic robust image segmentation, whereby accurate results are obtainable for a great variety of structures, and, more specifically, for a great variety of patient groups and health conditions. Further advantages of the computer program according to the invention will be discussed with reference to
These and other aspects of the invention will be discussed with reference to the following figures.
Number | Date | Country | Kind |
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05108790.6 | Sep 2005 | EP | regional |
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/IB2006/053141 | 9/7/2006 | WO | 00 | 8/6/2008 |