In our paper, we present a performance evaluation of image segmentation algorithms on microscopic image data. In spite of the existence of many algorithms for image data partitioning, there is no universal and 'the best' method yet. Moreover, images of microscopic samples can be of various character and quality which can negatively influence the performance of image segmentation algorithms. Thu...

Parasites live in a host and get its food from or at the expensive of that host. Cysts represent a form of resistance and spread of parasites. The manual diagnosis of microscopic stools images is time-consuming and depends on the human expert. In this paper, we propose an automatic recognition system that can be used to identify various intestinal parasite cysts from their microscopic digital i...

Characteristics of microscopic bone cross section images carry essential clues for defining the important features in the bone cross section such as harvesian canals, osteons, osteon fragments, lamellar bone, bony trabeculae, myxoid matrix and artifact for different age groups and also for age related developments & diseases. The traditional approaches of bone microscopic image analysis rely pr...

Characteristics of microscopic osteosarcoma bone cross section images carry essential clues for defining the important features in the bone cross section such as stroma, bone, malignant cell, myxoid matrix, artifact for different age groups and also for age related developments & diseases. The traditional approaches of bone microscopic image analysis rely primarily on manual processes with very...

The deep learning-based image segmentation approach has evolved into the mainstream of target detection and shape characterization in microscopic analysis. However, accuracy generalizability learning approaches are still hindered by insufficient data problem that results from high expense human material resources for acquisition annotation. Generally, augmentation can increase amount a short ti...