Semi-supervised segmentation of echocardiography videos via noise-resilient spatiotemporal semantic calibration and fusion.

We present a novel model for left ventricle endocardium segmentation from echocardiography video, which is of great significance in clinical practice and yet a challenging task due to (1) the severe speckle noise in echocardiography videos, (2) the irregular motion of pathological heart, and (3) the limited training data caused by high annotation cost. The proposed model has three compelling characteristics. First, we propose a novel adaptive spatiotemporal semantic calibration method to align the feature maps of consecutive frames, where the spatiotemporal correspondences are figured out based on feature maps instead of pixels, thereby mitigating the adverse effects of speckle noise in the calibration. Second, we further learn the importance of each feature map of neighbouring frames to the current frame from the temporal perspective so as to distinctively rather than uniformly harness the temporal information to tackle the irregular and anisotropic motions. Third, we integrate these techniques into the mean teacher semi-supervised architecture to leverage a large amount of unlabeled data to improve the segmentation accuracy. We extensively evaluate the proposed method on two public echocardiography video datasets (EchoNet-Dynamic and CAMUS), where the average dice coefficient on the left ventricular endocardium segmentation achieves 92.87% and 93.79%, respectively. Comparisons with state-of-the-art methods also demonstrate the effectiveness of the proposed method by achieving a better segmentation performance with a faster speed.

Quantum energy levels of glutamate modulate neural biophotonic signals.

Glutamate is the most abundant excitatory neurotransmitter in the brain, and it plays an essential and important role in neural functions. Current studies have shown that glutamate can induce neural biophotonic activity and transmission, which may involve the mechanism of photon quantum brain; however, it is unclear whether such a mechanism follows the principle of quantum mechanics. Here we show that the action of glutamate on its receptors leads to a decrease in its quantum energy levels, and glutamate then partially or completely loses its function to further induce the biophotonic activity in mouse brain slices. The reduced quantum energy levels of glutamate can be restored by direct-current electrical discharges and the use of energy transfer of chloroplast photosynthesis; hence, the quantum energy recovered glutamate can again induce significant biophotonic activity. Furthermore, the changes in quantum energy levels of glutamate are related to the exchange and transfer of electron energy on its active hydrogen atom. These findings suggest that the glutamate-induced neural biophotonic signals may be involved in the transfer of the quantum energy levels of glutamate, which implies a quantum mechanism of neurotransmitter action.

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain.

Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain.