The proposed method can be used to automatically quantify 3D cell morphology of plant tissue from micro-CT instead of opting for laborious manual annotations or less accurate segmentation approaches. In case fruit tissue porosity or pore network connectivity is too low or the specific surface area of the pore space too high, native X-ray micro-CT is unable to provide proper marker points of cell outlines, and one should rely on more elaborate contrast-enhancing scan protocols.
Keyphrases
- deep learning
- dual energy
- computed tomography
- convolutional neural network
- single cell
- contrast enhanced
- image quality
- high resolution
- cell therapy
- artificial intelligence
- magnetic resonance
- machine learning
- positron emission tomography
- stem cells
- mesenchymal stem cells
- resting state
- optical coherence tomography
- pet ct
- electron microscopy
- plant growth