The digital transformation in healthcare, propelled by the integration of deep learning
models and the Internet of Things (IoT), is creating unprecedented opportunities for …

Computational cytology is a critical, rapid-developing, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …

Cervical cancer is one of the most common cancers in daily life. Early detection and
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …

The resolution of current display devices is getting higher and higher, and 4K/8K display
devices have become popular, which require image super-resolution technologies to …

Fluorescence staining is an important technique in life science for labeling cellular
constituents. However, it also suffers from being time-consuming, having difficulty in …

Existing deep learning-based single-image super-resolution (SR) methods typically rely on
vast quantities of paired data. As an essential solution, zero-shot SR methods require only a …

Cervical cancer is one of the most common cancers among women, which seriously
threatens women's health. Early screening can reduce the incidence rate and mortality …

Cervical cancer is one of the most common cancers in daily life. Early detection and
diagnosis can effectively help facilitate subsequent clinical treatment and management. With …

Complicated image registration is a key issue in medical image analysis, and deep learning-
based methods have achieved better results than traditional methods. The methods include …

Many advanced deep convolutional neural network (DCNN) methods have proven their
efficacy in reconstructing the texture of super-resolution images (SR) from low-resolution …