Siu et al., 2023 - Google Patents
Optofluidic imaging meets deep learning: from merging to emergingSiu et al., 2023
- Document ID
- 17518360191250662671
- Author
- Siu D
- Lee K
- Chung B
- Wong J
- Zheng G
- Tsia K
- Publication year
- Publication venue
- Lab on a Chip
External Links
Snippet
Propelled by the striking advances in optical microscopy and deep learning (DL), the role of imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a quantitative “smart” engine. A suite of advanced optical microscopes now enables imaging …
- 238000003384 imaging method 0 title abstract description 166
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
- G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Meijering | A bird’s-eye view of deep learning in bioimage analysis | |
Isozaki et al. | AI on a chip | |
He et al. | Deep learning for biospectroscopy and biospectral imaging: state-of-the-art and perspectives | |
Antony et al. | Light microscopy applications in systems biology: opportunities and challenges | |
Siu et al. | Optofluidic imaging meets deep learning: from merging to emerging | |
Meijering et al. | Imagining the future of bioimage analysis | |
Melanthota et al. | Deep learning-based image processing in optical microscopy | |
Li et al. | An overview of organs-on-chips based on deep learning | |
Sun et al. | Deep learning‐based single‐cell optical image studies | |
Sengupta et al. | Intracranial hemorrhages segmentation and features selection applying cuckoo search algorithm with gated recurrent unit | |
MacNeil et al. | Plankton classification with high-throughput submersible holographic microscopy and transfer learning | |
Liimatainen et al. | Convolutional neural network-based artificial intelligence for classification of protein localization patterns | |
Park et al. | Single cell analysis of stored red blood cells using ultra-high throughput holographic cytometry | |
Yuan et al. | Phasetime: Deep learning approach to detect nuclei in time lapse phase images | |
Zhou et al. | Computer vision meets microfluidics: a label-free method for high-throughput cell analysis | |
Salem et al. | Yeastnet: Deep-learning-enabled accurate segmentation of budding yeast cells in bright-field microscopy | |
Sheneman et al. | Deep learning classification of lipid droplets in quantitative phase images | |
Choi et al. | Emerging machine learning approaches to phenotyping cellular motility and morphodynamics | |
Ghani et al. | Computer vision-based Kidney’s (HK-2) damaged cells classification with reconfigurable hardware accelerator (FPGA) | |
Zang et al. | Fast analysis of time-domain fluorescence lifetime imaging via extreme learning machine | |
JP7064720B2 (en) | Calculation device, calculation program and calculation method | |
Witmer et al. | Generative adversarial networks for morphological–temporal classification of stem cell images | |
Lee et al. | A hardware accelerated system for high throughput cellular image analysis | |
Zhao et al. | Characterize collective lysosome heterogeneous dynamics in live cell with a space-and time-resolved method | |
Tshimanga et al. | An overview of open source deep learning-based libraries for neuroscience |