Basis of image analysis for evaluating cell biomaterial interaction using brightfield microscopy
Medical imaging is a growing field that has stemmed from the need to conduct noninvasive
diagnosis, monitoring, and analysis of biological systems. With the developments and …
diagnosis, monitoring, and analysis of biological systems. With the developments and …
Effect of Preprocessing on Performance of Neural Networks for Microscopy Image Classification
Medical field depends heavily on understanding and analyzing microscopy images of cells
to better diagnose diseases, to evaluate the effectiveness of various medical treatments and …
to better diagnose diseases, to evaluate the effectiveness of various medical treatments and …
FASTER R-CNN for cell counting in low contrast microscopic images
Cell imaging is a difficult problem in medical imaging and the acquisition of unstained
frames to reduce the side effects makes this even more challenging. As the field of …
frames to reduce the side effects makes this even more challenging. As the field of …
Two-Stage Unsupervised Classification of Cell Health
Supervised learning for cell classification is one of the most used approaches on different
studies. However, due to lack of labelling datasets provided by experts, and the small …
studies. However, due to lack of labelling datasets provided by experts, and the small …
Evaluation of Cell Segmentation Using Pruning and Quantization
Cell segmentation is a challenging task due to the imaging modality employed, cell's
deformable construct and imaging settings. The use of Deep Neural Networks (DNN) has …
deformable construct and imaging settings. The use of Deep Neural Networks (DNN) has …