Computer-aided Diagnosis of Breast Elastography

Ultrasonography has been an important imaging technique for detecting breast tumors. As opposed tothe conventional B-mode image, the real-time tissue elastography by ultrasound is a new technique for imagingthe elasticity and applied to detect the stiffness of tissues. The red region of color elastography indicatesthe soft tissue and the blue one indicates the hard tissue. The harder tissue usually is classified as malignancy.In this paper, the authors proposed a computer-aided diagnosis( CAD) system on elastography tomeasure whether this system is effective and accurate to classify the tumor into benign and malignant. Accordingto the features of elasticity, the color elastography was transferred to hue, saturation, and value(HSV) color space and extracted meaningful features from hue images. Then the neural network was utilizedin multiple features to distinguish tumors. In this experiment, there are 180 pathology-proven cases including113 benign and 67 malignant cases used to examine the classification. The results of the proposedsystem showed an accuracy of 83.89 %, a sensitivity of 82.09 % and a specificity of 84.96 %. Compared withthe physician\u27s diagnosis, an accuracy of 78.33 %, a sensitivity of 53.73 % and a specificity of 92.92 %, theproposed CAD system had better performance. Moreover, the agreement of the proposed CAD system andthe physician\u27s diagnosis was calculated by kappa statistics, the kappa 0.64 indicated there is a fair agreementof observers

Software tool for contrast enhancement and segmentation of melanoma images based on human perception

In this paper we present a software tool for melanoma border detection (MBD). It has been designed to be incorporated in any Computer Aided Diagnosis Tool (CAD) for early detection of melanoma in mass screening programs. The tool is completely automatic, posses a user-friendly interface and does not require any specific hardware. The main steps followed by the implemented algorithm are: uneven illumination correction, color contrast improvement and color image segmentation. All of them are performed in the uniform color space CIE L * a * b * in order to achieve a complete adaptation to human color perception. The program is able to provide not only the final obtained segmentation result but also intermediate graphical outcomes, guiding the user in the process of melanoma detection. This simple, friendly but powerful interface can serve as a support for the medical personnel in the melanoma diagnostic process. The MBD software and some samples of the dermoscopy images used can be downloaded at http://cs.ntu. edu.pk/research.php

Sex-related differences in chromatic sensitivity

Generally women are believed to be more discriminating than men in the use of colour names and this is often taken to imply superior colour vision. However, if both X-chromosome linked colour deficient males (~8%) and females (<1%) as well as heterozygote female carriers (~15%) are excluded from comparisons, then differences between men and women in red-green colour discrimination have been reported as not being significant (e.g., Pickford, 1944; Hood et al., 2006). We re-examined this question by assessing the performance of 150 males and 150 females on the Colour Assessment and Diagnosis (CAD) test (Rodriguez-Carmona, 2005). This is a sensitive test that yields small colour detection thresholds. The test employs direction-specific, moving, chromatic stimuli embedded in a background of random, dynamic, luminance contrast noise. A four-alternative, forced-choice procedure is employed to measure the subject’s thresholds for detection of colour signals in 16 directions in colour space, while ensuring that the subject cannot make use of any residual luminance contrast signals. In addition, we measured the Rayleigh anomaloscope matches in a subgroup of 111 males and 114 females. All the age-matched males (30.8 ± 9.7) and females (26.7 ± 8.8) had normal colour vision as diagnosed by a battery of conventional colour vision tests. Females with known colour deficient relatives were excluded from the study. Comparisons between the male and female groups revealed no significant differences in anomaloscope midpoints (p=0.709), but a significant difference in matching ranges (p=0.040); females on average tended to have a larger mean range (4.11) than males (3.75). Females also had significantly higher CAD thresholds than males along the red-green (p=0.0004), but not along the yellow-blue discrimination axis. The differences between males and females in red-green discrimination may be related to the heterozygosity in X-linked cone photopigment expression common among females

Multi-function based modeling of 3D heterogeneous wound scaffolds for improved wound healing

This paper presents a new multi-function based modeling of 3D heterogeneous porous wound scaffolds to improve wound healing process for complex deep acute or chronic wounds. An imaging-based approach is developed to extract 3D wound geometry and recognize wound features. Linear healing fashion of the wound margin towards the wound center is mimicked. Blending process is thus applied to the extracted geometry to partition the scaffold into a number of uniformly gradient healing regions. Computer models of 3D engineered porous wound scaffolds are then developed for solid freeform modeling and fabrication. Spatial variation over biomaterial and loaded bio-molecule concentration is developed based on wound healing requirements. Release of bio-molecules over the uniform healing regions is controlled by varying their amount and entrapping biomaterial concentration. Thus, localized controlled release is developed to improve wound healing. A prototype multi-syringe single nozzle deposition system is used to fabricate a sample scaffold. Proposed methodology is implemented and illustrative examples are presented in this paper

Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe