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J Microsc ; 284(2): 103-117, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34254690


Microscopic observation of biological specimen smears is the mainstay of diagnostic pathology, as defined by the Digital Pathology Association. Though automated systems for this are commercially available, their bulky size and high cost renders them unusable for remote areas. The research community is investing much effort towards building equivalent but portable, low-cost systems. An overview of such research is presented here, including a comparative analysis of recent reports. This paper also reviews recently reported systems for automated staining and smear formation, including microfluidic devices; and optical and computational automated microscopy systems including smartphone-based devices. Image pre-processing and analysis methods for automated diagnosis are also briefly discussed. It concludes with a set of foreseeable research directions that could lead to affordable, integrated and accurate whole slide imaging systems.

Food Chem ; 355: 129547, 2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-33773454


The detection of food adulterants and toxicants can prevent a large variety of adverse health conditions for the global population. Through the process of rapid sensing enabled by deploying novel and robust sensors, the food industry can assist in the detection of adulterants and toxicants at trace levels. Sensor platforms which exploit graphene-based nanomaterials satisfy this requirement due to outstanding electrical, optical and thermal properties. The materials' facile conjugation with linkers and biomolecules along with the option for further enhancement using nanoparticles results in highly sensitive and selective sensing characteristics. This review highlights novel applications of graphene derivatives for detection covering three important approaches; optical, electrical (field-effect) and electrochemical sensing. Suitable graphene-based sensors for portable devices as point-of-need platforms are also presented. The future scope of these sensors is discussed to showcase how these emerging techniques will disrupt the food detection sector for years to come.

Análise de Alimentos/métodos , Contaminação de Alimentos/análise , Grafite/química , Eletricidade , Nanotecnologia
J Biophotonics ; 13(11): e202000123, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33245636


Low-cost automated histopathology microscopy systems usually suffer from optical imperfections, producing images that are slightly Out of Focus (OoF). In this work, a guided filter (GF) based image preprocessing is proposed for compensating focal errors and its efficacy is demonstrated on images of healthy and malaria infected red blood cells (h-RBCs and i-RBCs), and PAP smears. Since contrast enhancement has been widely used as an image preprocessing step for the analysis of histopathology images, a systematic comparison is made with six such prominently used methods, namely Contrast Limited Adaptive Histogram Equalization (CLAHE), RIQMC-based optimal histogram matching (ROHIM), modified L0, Morphological Varying(MV)-Bitonic filter, unsharp mask filter and joint bilateral filter. The images enhanced using GF approach lead to better segmentation accuracy (upto 50% improvement over native images) and visual quality compared to other approaches, without any change in the color tones. Thus, the proposed GF approach is a viable solution for rectifying the OoF microscopy images without the loss of the valuable diagnostic information presented by the color tone.

Algoritmos , Aumento da Imagem , Feminino , Humanos