Image Analysis and Image Mining Techniques: A Review

This paper presents the analysis of existing literature which is relevant to mining and the mechanisms associated with weighted substructure. Though, the literature consists of a lot many research contributions, but, here, we have analysed around thirty-five research and review papers. The existing approaches are categorized based on the basic concepts involved in the mechanisms. The emphasis is on the concept used by the concerned authors, the database used for experimentations and the performance evaluation parameters. Their claims are also highlighted. Our findings from the exhaustive literature review are mentioned along with the identified problems. This paper is useful for comparative study of various approaches which is prerequisite for solving image mining problem

Dual-channel active contour model for megakaryocytic cell segmentation in bone marrow trephine histology images

Assessment of morphological features of megakaryocytes (special kind of cells) in bone marrow trephine biopsies play an important role in the classification of different subtypes of Philadelphia-chromosome-negative myeloproliferative neoplasms (Ph-negative MPNs). In order to aid hematopathologists in the study of megakaryocytes, we propose a novel framework that can efficiently delineate the nuclei and cytoplasm of these cells in digitized images of bone marrow trephine biopsies. The framework first employs a supervised machine learning approach that utilizes color and texture features to delineate megakaryocytic nuclei. It then employs a novel dual-channel active contour model to delineate the boundary of megakaryocytic cytoplasm by using different deconvolved stain channels. Compared to other recent models, the proposed framework achieves accurate results for both megakaryocytic nuclear and cytoplasmic delineation

Novel miniaturised and highly versatile biomechatronic platforms for the characterisation of melanoma cancer cells

There has been an increasing demand to acquire highly sensitive devices that are able to detect and characterize cancer at a single cell level. Despite the moderate progress in this field, the majority of approaches failed to reach cell characterization with optimal sensitivity and specificity. Accordingly, in this study highly sensitive, miniaturized-biomechatronic platforms have been modeled, designed, optimized, microfabricated, and characterized, which can be used to detect and differentiate various stages of melanoma cancer cells. The melanoma cell has been chosen as a legitimate cancer model, where electrophysiological and analytical expression of cell-membrane potential have been derived, and cellular contractile force has been obtained through a correlation with micromechanical deflections of a miniaturized cantilever beam. The main objectives of this study are in fourfold: (1) to quantify cell-membrane potential, (2) correlate cellular biophysics to respective contractile force of a cell in association with various stages of the melanoma disease, (3) examine the morphology of each stage of melanoma, and (4) arrive at a relation that would interrelate stage of the disease, cellular contractile force, and cellular electrophysiology based on conducted in vitro experimental findings. Various well-characterized melanoma cancer cell lines, with varying degrees of genetic complexities have been utilized. In this study, two-miniaturized-versatile-biomechatronic platforms have been developed to extract the electrophysiology of cells, and cellular mechanics (mechanobiology). The former platform consists of a microfluidic module, and stimulating and recording array of electrodes patterned on a glass substrate, forming multi-electrode arrays (MEAs), whereas the latter system consists of a microcantilever-based biosensor with an embedded Wheatstone bridge, and a microfluidic module. Furthermore, in support of this work main objectives, dedicated microelectronics together with customized software have been attained to functionalize, and empower the two-biomechatronic platforms. The bio-mechatronic system performance has been tested throughout a sufficient number of in vitro experiments.Open Acces

PDES-BASED MORPHOLOGY ON GRAPHS FOR CYTOLOGICAL SLIDES SEGMENTATION AND CLUSTERING

In this paper, we propose a new graph-based approach to address the problem of cytological computer-aided diagnostic. Such approach uses our previously introduced formalism of PdEs-based morphology and geometric diffusion on graphs. The approach is illustrated through two applications in cytopathology (involving Feulgen and Papanicolaou colorations), with examples of nucleus extraction and classification. Index Terms — PdEs, weighted graphs, morphology, cytology, segmentation, classificatio

Neuroglia

This book is a compiled version of the journal Neuroglia. It was a peer-review Open Access journal by MDPI that investigated a wide range of glia related topics. Now the journal is published as a section of the journal Brain Sciences, with a new section Editor-in-Chief Prof. Sergey Kasparov