Acquiring/Recognising Microscopic Objects TRIZ Cases
- Beam-Homogenized Microscope for Uniform Multi-Well TIRF Imaging
A beam homogenizer shapes side-entry illumination through a prism to uniformly excite only the well bottom, reducing speckle and autofluorescence.
- Digital PCR Leakage Detection Using Partition Neighborhood Analysis
Machine learning analyzes neighboring partition fluorescence to detect digital PCR leakage faster and improve assay accuracy.
- Spectral Data Clustering for Multicolor Flow Cytometry
Logicle preprocessing and FlowSOM clustering handle multicolor flow cytometry data growth while reducing misclassification and analysis time.
- Cell Clustering With Traceable Fluorescence Data Mapping
Compressed flow cytometry data is linked back to original fluorescence measurements, enabling faster cell clustering with result verification.
- Regional Embeddings in Multiple-Instance Learning for Weakly Labeled Pathology
Regional and patch embeddings improve weakly labeled whole-slide pathology classification without time-consuming patch-level annotation.
- Cell Senescence Scoring from Nuclear Morphology Using Unsupervised Learning
Unsupervised analysis of nuclear morphology and cell image features identifies senescent cells more consistently across tissues and contexts.
- Dark-Field Microscopy Angle Control to Prevent Secondary Reflections
Calculated dark-field illumination angles prevent secondary reflections in specimen carriers, enabling clear unstained cell nucleus imaging.
- Contour Coordinate Reduction for Accurate Whole Slide Target Images
Uniformly reduced contour coordinates keep whole slide target images within size limits while preserving contour spacing and accuracy.
- Sperm Cell Characterization Using Defocused CNN Imaging
Defocused or lensless CNN imaging tracks sperm positions across image series to characterize motility and morphology with wide field coverage.
- Label-Free Macrophage Polarization Classification for Live-Cell Screening
Live-cell label-free imaging and machine learning classify macrophage polarization states in real time, reducing invasive, slow wet lab assays.
- Spectral Data Clustering with Logicle Preprocessing for Flow Cytometry
Logicle conversion and FlowSOM batch learning improve multicolor flow cytometry clustering accuracy while reducing spectral misclassification.