The treatment effect of ovarian cancer in clinical practice is poor, mainly because patients are often diagnosed with ovarian cancer in the middle and late stages when the cancer cells in the ...

Abstract: The use of deep learning in cancer detection has the potential to lead to more precise and timely diagnosis. In order to identify cancer, this study presents a deep learning-based picture ...

Spatial landmarks are crucial in describing histological features between samples or sites, tracking regions of interest in microscopy, and registering tissue samples within a common coordinate ...

Abstract: This study's objective is to evaluate the degree of accuracy of several machine learning algorithms for detecting early-stage lung cancer. A thorough investigation showed that certain ...

As a leading Open Access publisher, Frontiers is committed to empowering not only scientists, but other researchers, innovators and members of the public. As such, highlighting sustainable development ...

The objective of this COBRE is to establish a new biomedical imaging research center with appropriate infrastructure and research capacity along with a multidisciplinary mentoring team to support the ...

The present work aims to explore the performance of fuzzy system-based medical image processing for predicting the brain disease. The imaging mechanism of NMR (Nuclear Magnetic Resonance) and the ...

Pathologists have been largely diagnosing disease the same way for the past 100 years, by manually reviewing images under a microscope. But new work suggests that computers can help doctors improve ...