Reconstruction and rendering of microcalcifications from two mammogram views by modified projective grid space (MPGS)

Mammograms taken by two views: cranio-caudal (CC) and medio-lateral oblique (MLO) views provide only 2D projections of the microcalcifications, which lack the depth information. Thus, envisioning the relative lesion location from mammograms is a challenge for radiologists. To assist radiologists in locating and rendering lesion tissues, a modified projective grid space (MPGS) scheme is proposed to reconstruct 3D microcalcifications. The MPGS scheme reconstructs 3D microcalcifications in a unique space defined by corresponding points and the epipoles retrieved from the fundamental matrix of the CC and MLO views. Since only corresponding points of images are required in the proposed MPGS scheme, we can avoid the difficulty associated with most reconstruction approaches that require prior complicated calibration of X-ray machine. Considering the deformation of the breast, a new method based on the concept of bundle adjustment is proposed to rectify the 3D locations of reconstructed microcalcifications by uncompressed breast model reconstructed from the real patient body using MPGS scheme with iterative closest point (ICP). Then, the reconstructed microcalcifications are augmented in the real patient body model to show their relative positions.

[1]  Andrew W. Fitzgibbon,et al.  Bundle Adjustment - A Modern Synthesis , 1999, Workshop on Vision Algorithms.

[2]  Chien-Shun Lo,et al.  Automatic detection of microcalcifications in digital mammograms by entropy thresholding , 1996, Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[3]  Joseph Naor,et al.  Multiple Resolution Texture Analysis and Classification , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Michael Brady,et al.  Correspondence between different view breast X-rays using a simulation of breast deformation , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[5]  Joachim Dengler,et al.  Segmentation of microcalcifications in mammograms , 1991, IEEE Trans. Medical Imaging.

[6]  K. S. Arun,et al.  Least-Squares Fitting of Two 3-D Point Sets , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  William H. Press,et al.  Numerical recipes in C , 2002 .

[8]  Rae-Hong Park,et al.  An Orientation Reliability Matrix for the Iterative Closest Point Algorithm , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[10]  Heinz-Otto Peitgen,et al.  Scale-space signatures for the detection of clustered microcalcifications in digital mammograms , 1999, IEEE Transactions on Medical Imaging.

[11]  Takeo Kanade,et al.  Shape reconstruction in projective grid space from large number of images , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[12]  Yasuyo Kita,et al.  Three-dimensional reconstruction of microcalcification clusters from two mammographic views , 2001, IEEE Transactions on Medical Imaging.

[13]  J. M. Pruneda,et al.  Computer-aided mammographic screening for spiculated lesions. , 1994, Radiology.

[14]  Daniel B. Kopans,et al.  Digital Breast Tomosynthesis: Potentially a New Method for Breast Cancer Screening , 1998, Digital Mammography / IWDM.

[15]  Reinhard Klette,et al.  Computer vision - three-dimensional data from images , 1998 .

[16]  Olivier D. Faugeras,et al.  The fundamental matrix: Theory, algorithms, and stability analysis , 2004, International Journal of Computer Vision.

[17]  Jian Fan,et al.  Mammographic feature enhancement by multiscale analysis , 1994, IEEE Trans. Medical Imaging.

[18]  Rangaraj M. Rangayyan,et al.  Application of shape analysis to mammographic calcifications , 1994, IEEE Trans. Medical Imaging.

[19]  Chein-I Chang,et al.  A relative entropy-based approach to image thresholding , 1994, Pattern Recognit..

[20]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[21]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Zhengyou Zhang,et al.  Determining the Epipolar Geometry and its Uncertainty: A Review , 1998, International Journal of Computer Vision.

[23]  S Field,et al.  An investigation into why two-view mammography is better than one-view in breast cancer screening. , 2000, Clinical radiology.