Nuclei Segmentation on Histopathology Images of Breast Carcinoma.

With the use of computer-aided diagnostic systems, the automatic detection and segmentation of the cell nuclei have become essential in pathology due to cellular nuclei counting and nuclear pleomorphism analysis are critical for the classification and grading of breast cancer histopathology. This work describes a methodology for automatic detection and segmentation of cellular nuclei in breast cancer histopathology images obtained from the BreakHis database, the Standford tissue microarray database, and the Breast Cancer Cell Segmentation database. The proposed scheme is based on the characterization of Hematoxylin and Eosin (H&E) staining, size, and shape features. In addition, we use the information obtained from morphological transformations and adaptive intensity adjustments to detect and separate each cell nucleus detected in the image. The segmentation was carried out by testing the proposed methodology in a histological breast cancer database that provides the associated groundtruth segmentation. Subsequently, the Sørensen-Dice similarity coefficient was calculated to analyze the suitability of the results.Clinical relevance- In this work, the detection and segmentation of cell nuclei in breast cancer histological images are carried out automatically. The method can identify cell nuclei regardless of variations in the level of staining and image magnification. Moreover, a granulometric analysis of the components allows identifying cell clumps and segment them into individual cell nuclei. Improved identification of cell nuclei under different image conditions was demonstrated to reach a sensitivity average of 0.76 ± 0.12. The results provide a base for further and complex processes such as cell counting, feature analysis, and nuclear pleomorphism, which are relevant tasks in the evaluation and diagnostic performed by the expert pathologist.

Adaptive processing for noise attenuation in laser speckle contrast imaging.

BACKGROUND AND OBJECTIVE: Blood vessel visualization is an essential task to treat and evaluate diseases such as port-wine stain. Laser Speckle Contrast Imaging (LSCI) have applications in the analysis of the microvasculature. However, it is often limited to superficial depths because the tissue among skin and microvasculature introduces noise in the image. To analyze microvasculature, traditional LSCI methods compute a Contrast Image (CI) by using a shifting window of fixed size and shape, which is inadequate in images with structures different types of morphologies in it, as happens in LSCI. This work aims to reduce the noise in the CIs to improve the visualization of blood vessels at high depths (> 300 µ m). METHODS: The proposed method processes the CIs with analysis windows that change their size and shape for each pixel to compute the contrast representation with pixels more representatives to the region. RESULTS: We performed experiments varying the depth of the blood vessels, the number of frames required to compute the representation, and the blood flow in the blood vessel. We looked for an improvement in the Contrast to Noise Ratio (CNR) in the periphery of the blood vessels using an analysis of variance. Finding that the adaptive processing of the contrast images allows a significant noise attenuation, translated into a better visualization of blood vessels. An average CNR of 2.62 ± 1 and 5.26 ± 1.7 was reached for in-vitro and in-vivo tests respectively, which is higher in comparison with traditional LSCI approaches. CONCLUSIONS: The results, backed by the measured CNR, obtained a noise reduction in the CIs, this means a better temporal and spatial resolution. The proposed awK method can obtain an image with better quality than the state-of-the-art methods using fewer frames.

Density map and fuzzy classification for breast density by using BI-RADS.

Mammographic density (MD) is conformed by a different percentage of stromal, epithelial, and adipose tissue within the breast. One of the most critical findings in mammographic patterns for establishing a diagnosis of breast cancer is high breast tissue density. There is a wide variety of works focused on the study and automatic calculation of general breast density; however, they do not provide more detailed information about the changes that may occur within the breast tissue. This work proposes to generate a breast density map based on a texture analysis to identify the internal composition and distribution of the breast tissue through the diffuse division technique of the different densities inside the breast. Therefore, it is possible to obtain a density map associated with the breast that allows us to distinguish and quantify the different types of breast densities and their distribution according to the Breast Imaging Reporting and Data System (BI-RADS Breast Density Category). The proposed methodology was tested with mammograms from the BCDR and InBreast databases, demonstrating consistency in results and reaching an accuracy of 84.2% and 81.3%, respectively. Finally, the information obtained from the density map and its analysis could be a support tool for the specialist physician to monitor changes in breast density over time, since the fuzzy classification carried out allows quantifying the degree of membership in the BI-RADS breast density classes.

Quantitative estimation of temperature variations in plantar angiosomes: a study case for diabetic foot.

Thermography is a useful tool since it provides information that may help in the diagnostic of several diseases in a noninvasive and fast way. Particularly, thermography has been applied in the study of the diabetic foot. However, most of these studies report only qualitative information making it difficult to measure significant parameters such as temperature variations. These variations are important in the analysis of the diabetic foot since they could bring knowledge, for instance, regarding ulceration risks. The early detection of ulceration risks is considered an important research topic in the medicine field, as its objective is to avoid major complications that might lead to a limb amputation. The absence of symptoms in the early phase of the ulceration is conceived as the main disadvantage to provide an opportune diagnostic in subjects with neuropathy. Since the relation between temperature and ulceration risks is well established in the literature, a methodology that obtains quantitative temperature differences in the plantar area of the diabetic foot to detect ulceration risks is proposed in this work. Such methodology is based on the angiosome concept and image processing.

Análisis de la variación del calcio intracelular en células foliculares / Intracellular Calcium Variation Analysis of Follicular Cells

En este trabajo se presenta un método para medir la variación del calcio intracelular en células foliculares. Esta propuesta consiste en dos etapas: (i) La detección de los núcleos de las células; y (ii) el análisis de las variaciones de fluorescencia. La primera etapa se realiza a través de la transformada modificada de líneas divisoras de agua controlada por marcadores (en inglés: Modified-Watershed Transformation) controlando el proceso de etiquetado de células por el establecimiento de criterios particulares. El proceso de detección homogeniza las condiciones de luminosidad a través de un filtro morfológico y utiliza como descriptores a los bordes de las células. En la segunda etapa, se asocia la variación de la fluorescencia con los cambios de Ca2+ intracelular donde la variación se modela como una función exponencial decreciente. Luego, se presenta un nuevo proceso morfológico, denominado proceso de reconstrucción medio, que permite suavizar los datos para el proceso de modelado. Este proceso utiliza la información del sub modelado y sobre modelado de la señal, mediante las propiedades de los operadores de reconstrucción, conservando la estructura interna de la señal original. Finalmente, en un proceso experimental utilizando células de anfibios, se muestran los resultados obtenidos después de aplicar la propuesta a un grupo de células.

This paper presents a method for the measurement of the variation of intracellular calcium in follicular cells. This proposal consists in two stages: (i) The detection of the cell's nuclei, and (ii) the analysis of the fluorescence variations. The first stage is performed with the modified-watershed transformation, where the marker process is controlled by establishing own criterion. The detection process homogenizes the luminance conditions through a morphological filter and uses as descriptors the edges of the cells. In the second stage, the variations of fluorescence are associated with changes in intracellular Ca2+, which are modeled as an exponential decay function. Then, we present a new morphological process called medium reconstruction process, that smoothes the data in the process of model creation. This process uses the information of under and over model of the signal, through the properties of reconstruction operators, keeping the internal structure of the original signal. Finally, using amphibian cells in an experimental process, the results obtained are showed after applying the proposal to a group of cells.