Quantum Programming for Neuroradiology/Medical Imaging

Advancements in quantum programming performed on simulators and some real hardware provides expectancy for Neuroradiology applications such as Classification and Prediction to witness coding updates. (1-2)

Quantum Variational Circuits (QVCs), also referred to as Variational Quantum Circuits or Parametrized Quantum Circuits, have been used successfully in early applications, including two additional Alzheimer's Disease Radiology Classification studies. (3-4)

Another likely developer approach will be to modify conventional CNNs or add Quantum Convolutional Neural Networks (QCNNs) to take advantage of quantum entanglement and superpositioning. A Fully Connected Quantum Convolutional Neural Network (FCQ-CNN) has been used for Medical Data - for greater classification functionality. (5)

Additional programming alternatives exist in the form of scalable Quantum Convolutional Neural Networks (sQCNNs) and scalable Quantum Convolutional Neural Networks-3D (sQCNNs-3D) for point cloud images - Both offering the promise for lower numbers of qubits required; and therefore less "barren plateaus", when run on real quantum computers. (6-7)

Here, Kevin Kawchak will utilize literature and industry documentation to support running types of quantum codes for Neuroradiology and Medical Imaging applications regarding Alzheimer's Disease.

References:

Springer Nature Group, Nature Portfolio, MDPI, arxiv, IEEE, #cnn, #qcnn, #sqcnn, #sqcnn3d, #fcqcnn, #qml, #qnn, #ml, #ai, #barrenplateaus, #alzheimers, #dementia

Sincerely,
--
CEO Kevin Kawchak
ChemicalQDevice
Alzheimer's/Quantum
February 23rd, 2023

[alejandrogiraldo]

Amazing labor Kevin, teach and explain QC is a lil bit dificult, sometimes is difficult to understand the big picture for whom are not in the wave, but thanks for always creating content and meetings to surf!