Mesoscale microscopy images of the brain contain a wealth of information which can help
us understand the working mechanisms of the brain. However, it is a challenging task to …

Objective The aim of this study was to investigate whether a deep learning object detection
technique can automatically detect and classify radiolucent lesions in the mandible on …

The pathology is decisive for disease diagnosis but relies heavily on experienced
pathologists. In recent years, there has been growing interest in the use of artificial …

光学遥感图像船舶检测主要面临两个挑战: 光学遥感图像背景复杂, 船舶检测易受海浪,
云雾及陆地建筑等多方面干扰; 遥感图像分辨率低, 船舶目标小, 对于其分类与定位带来很大困难 …

The manual observation of sputum smears by fluorescence microscopy for the diagnosis
and treatment monitoring of patients with tuberculosis (TB) is a laborious and subjective …

Abnormal tau inclusions are hallmarks of Alzheimer's disease and predictors of clinical
decline. Several tau PET tracers are available for neurodegenerative disease research …

AnnotatorJ combines single-cell identification with deep learning (DL) and manual
annotation. Cellular analysis quality depends on accurate and reliable detection and …

Glaucoma is a disease associated with the loss of retinal ganglion cells (RGCs), and
remains one of the primary causes of blindness worldwide. Major research efforts are …

Object detection networks are high-performance algorithms famously applied to the task of
identifying and localizing objects in photography images. We demonstrate their application …

Stem cells represent an ideal source for regenerative medicine; however, longitudinal
assessment of stem cell phenotype and function is challenging. Contrastingly, a …