a preferred embodiment will be set forth in detail with reference to the drawings , in which like reference numerals refer to like elements or steps throughout . the first step is skin removal . although the skin in cbbct images has higher intensity than the fatty stroma , its intensity is only slightly higher than that of the glandular tissue . a simple thresholding cannot segment the skin from other tissue . based on the fact that the skin is on the outermost layer of the whole breast , a morphological process is proposed to remove the skin from the breast in cbbct images . 1 . a histogram thresholding method is applied to the whole cbbct image volume to separate the image into three distinct parts which have significant different intensities : air , fat and tissues ( including skin and glands ). 2 . based on the fact that the skin is between the inner breast and the air , a morphological 3d erosion operation is applied to erode the tissue between air and fat . 3 . when the erosion kernel reaches the fat area in the inner breast , the erosion stops . 4 . in case the glandular tissue is connected to the skin in cbbct images , during the erosion , a global ratio of fat area vs . total edge area is recorded along the edge of the breast . when the ratio reaches 80 % ( or another suitably chosen value ), the skin removal process stops . glandular tissue segmentation will now be explained . the fuzzy c - means ( fcm ) algorithm is widely used for image segmentation . it is also used for breast density assessment in both mammography and breast mri . in cbbct images , due to the high soft tissue contrast , fcm is also an effective algorithm to segment glandular tissue from fat . the fcm is taught in james c . bezdek , “ pattern recognition with fuzzy objective function algorithms ”, kluwer academic publishers , norwell , mass ., 1981 . in the fuzzy c - means clustering algorithm , an objective function is defined as : where x i is the data vector to be clustered , c j is the center vector of the jth cluster , u ij is the degree of the vector x i in the jth cluster , it is the fuzziness exponent , n is the number of total data vectors , and c is the number of total clusters , ∥*∥ is a distance function measuring the similarity between any data vector and cluster center . the fuzzy c - means clustering algorithm iteratively optimizes the objective function j m by updating u ij and c j with the algorithm stops when max ij {| u ij ( k + 1 − u ij k |}& lt ; ε , where ε is the termination parameter between 0 and 1 . the cluster number c is set to 3 . each cluster represents air , fat , and glands . bias areas include low density glandular tissue with attenuation ( as measured in hounsfeld units , or hu ) close to the fat and non - uniform areas caused by imaging artifacts . to achieve better accuracy of tissue segmentation , the bias areas need to be handled . in addition to the clusters for air , fat and glands , an extra cluster is used for bias areas . to further assign voxels in a bias area into the three clusters , the following process is used : 1 . a local contrast process is applied to the cbbct images after skin removal . the local contrast is based on the following equation : here , f ( x , y , z ) is the hu of a voxel at a position ( x , y , z ), and r is a local cube with size n × n × n . by this process , the non - uniform artifact is reduced . 2 . voxels in the bias area are extracted to go through a second clustering using the images from step 1 . the cluster number here is set to 3 . the cluster with the highest center value is considered to be glands , and the rest of clusters are considered to be fat . 3 . combine the clustering results from first clustering and second clustering to yield a final result of air , fat and gland segmentation . after the cbbct images are segmented into skin , fat and glands , the percentage of each tissue with respect to the whole breast volume can be calculated . from the cbbct clinical database , 5 patient data sets were selected for a preliminary experiment . each patient data set had its mammography records reviewed by a radiologist , and its breast density category was assigned based on the mammograms . the computer aided breast density evaluation was applied to the cbbct images of each patient . fig1 shows the mammograms and the cbbct slices of 4 cases used in this study , corresponding to the 4 bi - rads breast density categories . more specifically , that figure shows four clinical cases with mlo mammogram images and cbbct slice images . top row : mammography images ; bottom row : corresponding cbbct slices . left column : birads - 1 ( fatty ) breast ; middle left column : birads - 2 ( scattered ) breast ; middle right column : birads - 3 ( hetero dense ) breast ; right column : birads - 4 ( extreme dense ) breast . the cbbct breast density auto - evaluation process is applied to each of the clinical cases . fig2 shows the skin removal results , and fig3 shows the auto - segmentation results . more specifically , fig2 shows a ) original cbbct image , b ) cbbct image with skin removed , and c ) skin image . fig3 shows a ) original cbbct image with skin removed , b ) fat tissue area , and c ) glandular tissue area . based on the segmented image , the percentages of skin , fat , and glands could be acquired . table i lists the density measurement and compares it with the bi - rads category of each case . breast density changes over time . an increase in breast density is associated with greater risk of breast cancer , regardless of the original breast density measurement . accurate measurement over time s important for active surveillance of the breast density change . the breast density auto - evaluation provides accurate volumetric measurement to detect the changes of density ; hence timely cancer risk assessment can be possible . table i above gives the comparison result between cbbct breast density measurement and the mammography based bi - rads category . as can be seen from the table , there are obvious disagreements between those two systems , especially within breasts with higher density categories in bi - rads . measuring breast density with two - dimensional mammograms and true three - dimensional cbbct images can yield different results for the same breast . a new breast density measurement system may be defined based on cbbct images . the preferred embodiment is not limited to measuring breast density . mass detection and calcification detection will now be disclosed . the algorithm is taught in xiaohua zhang , ruola ning and dong yang , “ three dimensional breast masses auto detection in cone beam breast ct ,” proc . spie 2009 ; 7260 : 726027 . abnormal density and structural distortion are radiographic signs for radiologists to detect masses . in 3d cbbct images , breast masses are observed as congregated volumetric regions which have a denser structure than the surrounding normal tissues . malignant masses have irregular or spiculated margins , while benign masses usually have smooth margins . the high contrast of cbbct images reveals the density difference between tissues . a 3d mass detection algorithm takes advantage of high contrast resolution and the 3d characteristic of the cbbct images . in cbbct , high contrast resolution reveals the contrast changes of tissue components across voxels . the 3d detection algorithm is able to measure these changes and uses the difference between masses and normal tissues for suspicious region detection . according to the preliminary study on 14 pathology - proven masses , after image calibration , the average contrast between masses and their surrounding tissues ranged from 10 to 80 hu . other characteristics , such as the gradient congregation of the mass , were also used to distinguish mass from normal tissue . in the preliminary studies , a 3d weighted average algorithm was applied , followed by a 3d iris filtering to cbbct volume images to highlight the congregate tissue volume . the highlighted areas are selected as candidates of breast masses . in the preliminary result , 12 of the 14 masses were correctly detected . after the mass regions are detected , the corresponding measurements of each region are calculated . the measurements include density , size , volume and shape descriptors . the marked results and corresponding measurements will be provided as output results . fig4 shows the results of preliminary studies on mass detection . images ( a ) and ( c ) show pathology - proven masses . images ( b ) and ( d ) show the results of automatic mass detection . calcification detection will now be disclosed . the algorithm is taught in xiaohua zhang , ruola ning and jiangkun liu , “ computer aided breast calcification auto - detection in cone beam breast ct ,” proc . spie 2010 ; 7624 : 76242m . in cbbct images , calcifications have high contrast to the surrounding tissues and high hu variations both inside the calcification area and at the edges . the contrast between calcification and background material is from − 200 hu to − 800 hu , and the hu standard deviation can be more than 200 hu . a calcification auto - detection scheme has been developed to locate the calcifications within cbbct images . a 3d local thresholding process and a histogram thresholding process are first applied to the cbbct images to select all voxels with relatively high hu value and hu variation with respect to the neighborhood voxels . to further reduce false positives , six features are extracted from each remaining connected voxel object . the features are fed into an artificial neural network ( ann ) which is trained with known calcification features . the ann output values are used as criteria to differentiate calcification objects from false positive objects . a preliminary study achieves sensitivity of 95 % with average 10 false positives calcifications per case . fig5 illustrates one example of cbbct calcification auto - detection , in which image ( a ) indicates known calcifications and image ( b ) indicates the results of the calcification algorithm . after the detection , measurements of the calcifications will be provided , including cluster size , number of calcifications in clusters and shape descriptors . breast ducts and blood vessels can be segmented . segmenting algorithms are known in the art , e . g ., for segmenting colons . a suitable algorithm is taught in d chen , r fahmi , a a farag , r l falk , o w dryden , “ accurate and fast 3d colon segmentation in ct colonography ,” proc . of isbi 2009 ; 490 - 493 . such segmentation can be used for active surveillance of duct carcinoma in situ ( dics ) and abnormal vasculature relating to tumors . artifact correction will now be disclosed . a suitable method is taught in ning r : apparatus and method for x - ray scatter reduction and correction for fan beam and cone beam volume ct . u . s . pat . no . 6 , 618466 issued on sep . 9 , 2003 and pct / us03 / 04871 . scattering is one of the major problems that are associated with cbbct because the large - area flat - panel detector in a cbbct system receives scattered x - rays as well as primary x - rays . at 49 kvp , the scatter - to - primary ratio can be as high as 0 . 5 for an average - sized breast . scattering produces inaccurate ct numbers , reduces tissue contrast and causes cupping artifact in the reconstructed cbbct images . given the roughly symmetric geometry of a breast and the slowly varying nature of scattered radiation , the scattered radiation is estimated based on the breast shape in a projection image , and the projection image is corrected by subtracting the scattered radiation . as the shape and position and breast shadow are different across different projection images , such a correction is performed for all projections . the axial and longitude uniformity can be improved to 20 hu and 40 hu respectively . motion artifacts are associated with patient movement and breathing during the scan , appearing as blurs in the reconstruction images . usually , the moment of motion can be identified by examining projection images . the data before or after this moment can be considered as motion - free data which can be used for reconstruction with half scan algorithms . a suitable algorithm is taught in dong yang , ruola ning , yong yu , david conover and xiartghua lu , “ implementation and evaluation of the half - scan scheme based on cbct ( cone - beam ct ) system ” proc . spie 5368 , 542 ( 2004 ). this method can efficiently remove motion artifacts . a system on which the preferred or another embodiment can be implemented is set forth in u . s . pat . no . 6 , 480 , 565 , whose disclosure is hereby incorporated by reference in its entirety into the present disclosure . fig2 a of that patent , which is reproduced herein as fig6 , shows an exemplary device . in the scanner 200 , the patient p rests on an ergonomically formed table 202 so that the breast b to be scanned descends through a hole 204 in the table 202 into a safety cover 205 . below the table 202 , a gantry 206 supports a detector 208 and an x - ray tube 210 , one on either side of the safety cover 205 . the gantry is turned by a motor 212 to be rotatable around an axis a passing through the safety cover 205 , so that as the x - ray tube travels along an orbit o , the breast b remains in the path of a cone beam c emitted by the x - ray tube 210 . the gantry is also movable by a motor 214 to go up and down along a vertical path v . alternatively , the table 202 can be moved up and down along a vertical path v . the detector 208 can be moved toward and away from the axis a by a motor 216 to change the magnification factor if necessary . in some embodiments , a piston 218 may be used to push the nipple toward the chest wall to reduce z - direction coverage by a couple of centimeters , although usually , the breast does not have to be re - shaped . a contrast injector 220 can be provided for contrast enhanced tomographic imaging , angiogenesis studies and some other dynamic contrast studies . various contrast injection media , such as iodine , are known in the art . it is not always necessary to inject a contrast medium into the patient . the cbbct - cad software / hardware includes the modules shown in fig7 : image artifact correction modules : the image artifact correction modulus are executed either before or after the cbbct reconstruction . as shown , the modules include pre - correction 704 and post - correction 708 . the pre - correction is performed on the projections acquired from the cbbct scan . a suitable method is taught in ning r : apparatus and method for x - ray scatter reduction and correction for fan beam and cone beam volume ct . u . s . pat . no . 6 , 618466 issued on sep . 9 , 2003 and pct / us03 / 04871 . the post - correction is performed on the isotropic 3d images from the cbbct reconstruction . detection and segmentation modules : the four detection and segmentation modules are interconnected . those modules are density assessment 710 , duct segment detection 712 , calcification detection 714 , and mass detection 716 . the density assessment algorithm has been described above . a suitable calcification detection algorithm is taught in xiaohua zhang ruola ning and jiangkun liu , “ computer aided breast calcification auto - detection in cone beam breast ct ,” proc . spie 2010 ; 7624 : 76242m . a suitable mass detection algorithm is taught in xiaohua zhang , ruola ning and dong yang , “ three dimensional breast musses auto detection in cone beam breast ct ,” proc . spie 2009 ; 7260 : 726027 . the users are able to choose one or multiple modules for better diagnostic assistance . each of the modules is designed to run on both the cpu and the gpu to reduce the processing time . the output results of each module can be superimposed so that radiologists can combine different information to make an accurate decision . the task manager 718 is the main interface of the cad system between the users and the cad modules . system connections , data send / receive configurations and task scheduling / queuing are defined through the task manager . the task manager organizes all applicable cases and dispatches the tasks to the detection and segmentation modules based on the specific requirements for each case . the task manager also plans all possible resources in the system and assigns the resource to the appropriate modules . data access interface 720 : this is a dicom interface to pacs / image archive system 722 for image data retrieve / store and the radiologists &# 39 ; feedback , annotation or report , for further processing . multiple dicom outputs , including dicom printers , structured reporting , dicom 6000 overlay , secondary image capture and rtss are supported . fig8 shows the hardware structure of the cbbct cad system , based on the system of the above - cited &# 39 ; 565 patent or any other suitable system . three major hardware components will be included in the cad system : cad server 802 : the cad server provides the interface for all clients and external pacs 722 or image archive systems 804 , as well as dicom printers 806 . it is equipped with highly configured parts to provide fast and reliable services . the cad server accepts the schedules from pre - configured tasks or the user inputs , read data from the pacs / archive system , dispatches the computation tasks to the cad workstations , receives the result from the workstations and rites the cad reports back to the pacs / archive system or prints the reports . cad workstation 808 : the major functional modules of the cad system are running on the high performance workstation . it provides fast and reliable computation to satisfy the practical requirements . the workstation is attached to the server by hi - speed connection . multiple workstations can be installed and connected in each system to perform the tasks parallelly to provide enough computation capability . thin client 810 : the thin client gives users easy access to the system . it can be browser - based application or stand - alone gui application . it communicates with the cad server within the intranet or over the internet to provide the services from anywhere : with internet connection . the users setup the configurations and schedule tasks on the cad server through the intuitive gui provided by the thin client . with the parallel processing capability of the hardware and software design , the total processing time of the cbbct - cad system is expected to be within 5 minutes . while a preferred embodiment has been set forth in detail above , those skilled in the art who have reviewed the present disclosure will readily appreciate that other embodiments can be realized within the scope of the invention . for example , recitations of specific hardware and of numerical values are illustrative rather than limiting . in addition , the disclosed cone beam ct image - based cad method and system can be used for other cone beam ct imaging applications , such as angiography imaging and lung imaging . therefore , the present invention should be construed as limited only by the appended claims .