Abstract: A system, method, software arrangement and computer-accessible medium for performing electronic cleansing of CT colonography images are provided. In this system, method, software arrangement and computer-accessible medium, the digital bowel cleansing can be performed to remove tagged bowel contents from the images. The digital bowel cleansing can apply a local shape analysis throughout the images and use a shape-based speed function to detect the folds and polyps structures while removing the tagged bowel contents region. The system, method, software arrangement and computer-accessible medium can enable a medical examiner to perform an accurate virtual colonoscopy on a patient, without the need for thorough patient preparation.

Abstract: A system, method, software arrangement and computer-accessible medium for performing electronic cleansing of CT colonography images are provided. In this system, method, software arrangement and computer-accessible medium, the digital bowel cleansing can be performed to remove tagged bowel contents from the images. The digital bowel cleansing can apply a local shape analysis throughout the images and use a shape-based speed function to detect the folds and polyps structures while removing the tagged bowel contents region. The system, method, software arrangement and computer-accessible medium can enable a medical examiner to perform an accurate virtual colonoscopy on a patient, without the need for thorough patient preparation.

Abstract: A lumen tracking method and system automatically extracts a colon from CT image data by locating landmarks in the image data, based on known anatomic features or other predictable features. If the colon is segmented, the method and system may use the landmarks to evaluate candidate segments for inclusion in the extracted colon.

Abstract: An adaptive density correction (ADC) method and system automatically compensate for pseudo-enhancement (PEH) of voxels in computed tomography (CT) data, such as in fecal-tagged CT colonography (ftCTC), so air (or another low-contrast background) and soft tissues are represented by their usual CT attenuations. ADC estimates an amount of pseudo-enhancement energy that was received by voxels that are near tagged voxels (i.e., voxels that are tagged with a high-contrast agent), based on a first distribution scheme, such as a Gaussian distribution. ADC then iteratively distributes PEH energy received by voxels to neighboring voxels, according to another distribution scheme, which may be another Gaussian function. ADC then subtracts the total amount of PEH energy at each voxel from the CT data of the voxel.

Abstract: An adaptive density mapping (ADM) method and system automatically identify interface regions between air and material tagged with contrast agents in computed tomographic (CT) image data, then map CT attenuations of voxels outside the identified interface regions, such that voxels that represent tagged material are made to represent air or another gas.

Abstract: A system for performing a virtual colonoscopy includes a system for generating digital images, a storage device for storing the digital images, a digital bowel subtraction processor coupled to receive images of a colon from the storage device and for removing the contents of the colon from the image and an automated polyp detection processor coupled to receive images of a colon from the storage device and for detecting polyps in the colon image.