Examination of tissue biopsy and quantification of the various characteristics of cellular
processes are clinical benchmarks in cancer diagnosis. Nuclei and glands instance …

Segmentation of white blood cells in digital haematology microscope images represents one
of the major tools in the diagnosis and evaluation of blood disorders. Pathological …

Histological tissue images typically exhibit very sophisticated spatial color patterns. It is of
great clinical importance to extract qualitative and quantitative information from these …

Ninety years after its invention, the Pap test continues to be the most used method for the
early identification of cervical precancerous lesions. In this test, the cytopathologists look for …

Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …

Abstract Machine learning has attracted increasing interest in medical image computing and
computer-assisted intervention, and plays an important role in image-based computer-aided …

With applications in object detection, image feature extraction, image classification, and
image segmentation, artificial intelligence is facilitating high-throughput analysis of image …

Accurate cell segmentation is essential for computer-aided diagnosis of cervical
precancerous lesions in cytology images. Automated segmentation poses a great challenge …

Computerized image analysis of biological cells and tissues is a necessary complement to
high-throughput microscopy, allowing researchers to effectively analyze large volumes of …

The digitalization of pathology slides introduced a new era to pathology. Despite being the
most powerful prognostic tool, automated analysis of microscopic images is still not used in …