A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification
A computer-aided diagnosis (CAD) system requires detection, segmentation, and
classification in one framework to assist radiologists efficiently in an accurate diagnosis. In …
classification in one framework to assist radiologists efficiently in an accurate diagnosis. In …
A deep learning approach for the analysis of masses in mammograms with minimal user intervention
We present an integrated methodology for detecting, segmenting and classifying breast
masses from mammograms with minimal user intervention. This is a long standing problem …
masses from mammograms with minimal user intervention. This is a long standing problem …
Pdam: A panoptic-level feature alignment framework for unsupervised domain adaptive instance segmentation in microscopy images
In this work, we present an unsupervised domain adaptation (UDA) method, named
Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation …
Panoptic Domain Adaptive Mask R-CNN (PDAM), for unsupervised instance segmentation …
A feature transfer enabled multi-task deep learning model on medical imaging
Object detection, segmentation, and classification are three common tasks in medical image
analysis. Multi-task deep learning (MTL) tackles these three tasks jointly, which provides two …
analysis. Multi-task deep learning (MTL) tackles these three tasks jointly, which provides two …
[HTML][HTML] Automatic mitochondria segmentation for EM data using a 3D supervised convolutional network
C Xiao, X Chen, W Li, L Li, L Wang, Q Xie… - Frontiers in …, 2018 - frontiersin.org
Recent studies have supported the relation between mitochondrial functions and
degenerative disorders related to ageing, such as Alzheimer's and Parkinson's diseases …
degenerative disorders related to ageing, such as Alzheimer's and Parkinson's diseases …
[HTML][HTML] Automatic reconstruction of mitochondria and endoplasmic reticulum in electron microscopy volumes by deep learning
J Liu, L Li, Y Yang, B Hong, X Chen, Q Xie… - Frontiers in …, 2020 - frontiersin.org
Together, mitochondria and the endoplasmic reticulum (ER) occupy more than 20% of a
cell's volume, and morphological abnormality may lead to cellular function disorders. With …
cell's volume, and morphological abnormality may lead to cellular function disorders. With …
A guided tour of selected image processing and analysis methods for fluorescence and electron microscopy
Microscopy imaging, including fluorescence micro scopy and electron microscopy, has
taken a prominent role in life science research and medicine due to its ability to investigate …
taken a prominent role in life science research and medicine due to its ability to investigate …
EM-net: Deep learning for electron microscopy image segmentation
A Khadangi, T Boudier… - 2020 25th international …, 2021 - ieeexplore.ieee.org
Recent high-throughput electron microscopy techniques such as focused ion-beam
scanning electron microscopy (FIB-SEM) provide thousands of serial sections which assist …
scanning electron microscopy (FIB-SEM) provide thousands of serial sections which assist …
Contrastive learning for mitochondria segmentation
Mitochondria segmentation in electron microscopy images is essential in neuroscience.
However, due to the image degradation during the imaging process, the large variety of …
However, due to the image degradation during the imaging process, the large variety of …
Automatic detection and segmentation of mitochondria from SEM images using deep neural network
J Liu, W Li, C Xiao, B Hong, Q Xie… - 2018 40th Annual …, 2018 - ieeexplore.ieee.org
Investigating the link between mitochondrial function and its physical structure is a hot topic
in neurobiology research. With the rapid development of Scanning Electron Microscope …
in neurobiology research. With the rapid development of Scanning Electron Microscope …