A survey on applications of deep learning in microscopy image analysis
Z Liu, L Jin, J Chen, Q Fang, S Ablameyko, Z Yin… - Computers in biology …, 2021 - Elsevier
Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …
Machine‐learning‐assisted intelligent imaging flow cytometry: A review
Imaging flow cytometry has been widely adopted in numerous applications such as optical
sensing, environmental monitoring, clinical diagnostics, and precision agriculture. The …
sensing, environmental monitoring, clinical diagnostics, and precision agriculture. The …
Inception v3 based cervical cell classification combined with artificially extracted features
N Dong, L Zhao, CH Wu, JF Chang - Applied Soft Computing, 2020 - Elsevier
Traditional cell classification methods generally extract multiple features of the cell manually.
Moreover, the simple use of artificial feature extraction methods has low universality. For …
Moreover, the simple use of artificial feature extraction methods has low universality. For …
Cross-domain contrastive learning for hyperspectral image classification
P Guan, EY Lam - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Despite the success of deep learning algorithms in hyperspectral image (HSI) classification,
most deep learning models require a large amount of labeled data to optimize the numerous …
most deep learning models require a large amount of labeled data to optimize the numerous …
Classification of human white blood cells using machine learning for stain‐free imaging flow cytometry
M Lippeveld, C Knill, E Ladlow, A Fuller… - Cytometry Part …, 2020 - Wiley Online Library
Imaging flow cytometry (IFC) produces up to 12 spectrally distinct, information‐rich images of
single cells at a throughput of 5,000 cells per second. Yet often, cell populations are still …
single cells at a throughput of 5,000 cells per second. Yet often, cell populations are still …
Automatic identification of breast ultrasound image based on supervised block-based region segmentation algorithm and features combination migration deep …
WX Liao, P He, J Hao, XY Wang… - IEEE journal of …, 2019 - ieeexplore.ieee.org
Breast cancer is a high-incidence type of cancer for women. Early diagnosis plays a crucial
role in the successful treatment of the disease and the effective reduction of deaths. In this …
role in the successful treatment of the disease and the effective reduction of deaths. In this …
Immunology driven by large-scale single-cell sequencing
The immune system encompasses a large degree of phenotypic diversity and plasticity in its
cell types, and more is to be uncovered. We argue that large, multiomic datasets of single …
cell types, and more is to be uncovered. We argue that large, multiomic datasets of single …
Data‐driven intelligent manipulation of particles in microfluidics
Automated manipulation of small particles using external (eg, magnetic, electric and
acoustic) fields has been an emerging technique widely used in different areas. The …
acoustic) fields has been an emerging technique widely used in different areas. The …
Toward deep biophysical cytometry: prospects and challenges
The biophysical properties of cells reflect their identities, underpin their homeostatic state in
health, and define the pathogenesis of disease. Recent leapfrogging advances in …
health, and define the pathogenesis of disease. Recent leapfrogging advances in …
A self-learning deep neural network for classification of breast histopathological images
The most effective and feasible method for treating cancer is early diagnosis of breast
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …
cancer. An appropriate software tool, known as computer-aided diagnosis, helps doctors …