Recent Advances in Biomedical Image Segmentation Using Neural Networks

Cecilia Irene Loeza Mejía, Balzhoyt Roldán Ortega, Rajesh Roshan Biswal, Gregorio Fernández Lambert, D. Reyes González
2020 Research in Computing Science  
In recent years, the analysis and processing of biomedical images had considerable relevance, as it has proven to be an effective way of obtaining information regarding human body in a less invasive way and thus helps in extracting the characteristics that could potentially represent a disease. Different aspects of segmentation algorithms and features have been largely studied in the last decade relating to various areas. However, there is not a single method or solution because of the
more » ... in the property of images, medical imaging techniques and modalities, variability and noise for each object of interest. This work presents a comparison of different methods including deep learning for segmentation of multimodal biomedical images. In addition, the application of U-Net architecture for the lung region segmentation of chest computed tomography in the Lung TIME dataset was evaluated.
dblp:journals/rcs/MejiaOBLG20 fatcat:bun3iweysvgbtlocyxgbrzyjcy