Differential convolution for medical diagnosis

This paper describes differential convolution and its application to high-resolution three dimensional medical images to distinguish between normal and diseased tissue. Underlying image processing principles are presented focusing on texture analysis and prototype application of three dimensional convolution to identify normal, benign and malignant tissue.

[1]  Hans Knutsson,et al.  Filtering and reconstruction in image processing , 1984 .

[2]  Paolo P. Provenzano,et al.  Collagen reorganization at the tumor-stromal interface facilitates local invasion , 2006, BMC medicine.

[3]  Ernest L. Hall,et al.  Texture Measures for Automatic Classification of Pulmonary Disease , 1972, IEEE Transactions on Computers.

[4]  C Kimme-Smith,et al.  Using tissue texture surrounding calcification clusters to predict benign vs malignant outcomes. , 1996, Medical physics.

[5]  Irwin Edward Sobel,et al.  Camera Models and Machine Perception , 1970 .

[6]  John S. Condeelis,et al.  Identification and Testing of a Gene Expression Signature of Invasive Carcinoma Cells within Primary Mammary Tumors , 2004, Cancer Research.

[7]  Watt W Webb,et al.  Interpreting second-harmonic generation images of collagen I fibrils. , 2005, Biophysical journal.

[8]  C. Peters,et al.  Generation of optical harmonics , 1961 .

[9]  Fabrizio Argenti,et al.  Fast calculation of co-occurrence matrix parameters for image segmentation , 1990 .

[10]  M W Vannier,et al.  Three dimensional CT reconstruction images for craniofacial surgical planning and evaluation. , 1984, Radiology.

[11]  F. Winsberg,et al.  Detection of Radiographic Abnormalities in Mammograms by Means of Optical Scanning and Computer Analysis , 1967 .

[12]  John W. Woods,et al.  Multidimensional Signal, Image and Video Processing and Coding [Book Reviews] , 2007, IEEE Signal Processing Magazine.

[13]  J. Segall,et al.  Intravital imaging of cell movement in tumours , 2003, Nature Reviews Cancer.

[14]  M. Giger,et al.  Computerized characterization of mammographic masses: analysis of spiculation. , 1994, Cancer letters.

[15]  Carl Friedrich Gauss.  Theoria motus corporum coelestium , 1981 .

[16]  Peter D. Welch,et al.  Fast Fourier Transform , 2011, Starting Digital Signal Processing in Telecommunication Engineering.

[17]  L. Weiss.  Early Concepts of Cancer , 2000, Cancer Metastasis Review.

[18]  R A Robb,et al.  Interactive display and analysis of 3-D medical images. , 1989, IEEE transactions on medical imaging.