Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (R...
Computer methods and programs in biomedicine
Jul 9, 2019
BACKGROUND AND OBJECTIVES: The multi-label Human Protein Atlas (HPA) classification can yield a better understanding of human diseases and help doctors to enhance the automatic analysis of biomedical images. The existing automatic protein recognition...
As a typical biomedical detection task, nuclei detection has been widely used in human health management, disease diagnosis and other fields. However, the task of cell detection in microscopic images is still challenging because the nuclei are common...
We use Raman microscopic images with high spatial and spectral resolution to investigate differences between human follicular thyroid (Nthy-ori 3-1) and follicular thyroid carcinoma (FTC-133) cells, a well-differentiated thyroid cancer. Through compa...
Early detection of cervical lesion is of great significance in reducing mortality from cervical cancer, and segmentation of cervical cell nuclei plays an important role in screening for cervical lesion. Compared with traditional algorithms, several d...
In the detection of myeloproliferative, the number of cells in each type of bone marrow cells (BMC) is an important parameter for the evaluation. In this study, we propose a new counting method, which consists of three modules including localization,...
IEEE transactions on bio-medical engineering
Feb 22, 2019
OBJECTIVE: Nucleus recognition is a critical yet challenging step in histopathology image analysis, for example, in Ki67 immunohistochemistry stained images. Although many automated methods have been proposed, most use a multi-stage processing pipeli...
International journal of computer assisted radiology and surgery
Feb 16, 2019
PURPOSE: Cancers are almost always diagnosed by morphologic features in tissue sections. In this context, machine learning tools provide new opportunities to describe tumor immune cell interactions within the tumor microenvironment and thus provide p...
Cell nuclei detection is a challenging research topic because of limitations in cellular image quality and diversity of nuclear morphology, i.e., varying nuclei shapes, sizes, and overlaps between multiple cell nuclei. This has been a topic of enduri...
Toxicity is an important factor in failed drug development, and its efficient identification and prediction is a major challenge in drug discovery. We have explored the potential of microscopy images of fluorescently labeled nuclei for the prediction...