ChemicalQDeviceFDA Radiology and Quantum Algorithms
Dear Healthcare Colleague, my name is Kevin Kawchak, and I am the Founder CEO of ChemicalQDevice. Today is March 3rd, 2023 for "FDA Radiology Reconstruction and Segmentation Algorithms, Quantum Potential"
On October 5th 2022, FDA published an update to their Artificial Intelligence and Machine Learning-Enabled Medical Device Records. The 521 Approvals illustrates the progression of standard AI/ML algorithms to more advanced Deep Learning based solutions, in recent years. [1]
ChemicalQDevice published a PRISMA study on January 19th, 2023 that included 191 of these 521 approvals listed under Radiology or Neurology, and that showed benefit to the Brain/Head/or Skull. From this list, Several Key Areas were identified that illustrated the promise for Future Quantum Incorporation. [2]
Two of these FDA Areas include Deep Learning Reconstruction, and Automatic/Semi-Automatic Segmentation Algorithms - Both were further detailed on March 2nd, 2023. 15 of the 191 approvals were identified that have been implemented for Reconstruction in CT or MR scanners. [3]
A specific technology that offers potential benefit to reconstruction is found in MIT's publication by Kiani, B.T., et al. in 2020 titled "Quantum Medical Imaging Algorithms". The authors described prospective "exponential speedup over classical counterparts when data is input as a quantum state." [4]
In addition, benefit with reconstruction algorithms may be realized in emerging quantum hardware such as Ion Trap from IonQ, and a new CPU/GPU/QPU platform from NVIDIA. [5-6]
For Segmentation, 27 of the 191 FDA Approvals were identified that have been implemented for multi-modal applications. Quantum Inspired Neural Networks have been utilized in recent years that have had performance improvements over previous quantum results, yielding good Hippocampus segmentation. [7-8]
In addition, today's segmentation algorithms may see improvement through hybrid quantum neural networks that have ability to run larger data sets; Or require smaller training data sets to function, in specific cases. [9-13]
Quantum computing continues to improve regarding the number and quality of quantum bits. Regulatory organizations such as IEC and ISO look to close voting on quantum security standards, and will likely move to approve quantum technologies regarding new application areas, such as life sciences. [14-15]
References are available in the comments below. Have a productive rest of your day.
Smile at end!
3/3/23 "FDA Radiology Reconstruction and Segmentation Algorithms, Quantum Potential" References[1] https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices[2] https://www.chemicalqdevice.com/fda-aiml-approvals-basis-for-qnn-neuroimaging[3] https://www.chemicalqdevice.com/brain-disorders-and-quantum-computing[4] https://arxiv.org/abs/2004.02036[5] https://ionq.com/best-practices [6] https://developer.nvidia.com/qoda[7] https://link.springer.com/article/10.1007/s10489-021-03108-5 [8] https://link.springer.com/article/10.1007/s10489-021-02688-6[9] https://www.nature.com/articles/s41567-019-0648-8 [10] https://arxiv.org/abs/2210.09728 [11] https://arxiv.org/abs/2202.11204 [12] https://arxiv.org/abs/2301.08167 [13] https://www.nature.com/articles/s41467-022-32550-3[14] https://www.iso.org/standard/77097.html [15] https://www.iso.org/standard/77309.html
Created by Kevin Kawchak Founder CEO ChemicalQDevice2022 San Diego, CaliforniaAdvancing Neuroimaging
On October 5th 2022, FDA published an update to their Artificial Intelligence and Machine Learning-Enabled Medical Device Records. The 521 Approvals illustrates the progression of standard AI/ML algorithms to more advanced Deep Learning based solutions, in recent years. [1]
ChemicalQDevice published a PRISMA study on January 19th, 2023 that included 191 of these 521 approvals listed under Radiology or Neurology, and that showed benefit to the Brain/Head/or Skull. From this list, Several Key Areas were identified that illustrated the promise for Future Quantum Incorporation. [2]
Two of these FDA Areas include Deep Learning Reconstruction, and Automatic/Semi-Automatic Segmentation Algorithms - Both were further detailed on March 2nd, 2023. 15 of the 191 approvals were identified that have been implemented for Reconstruction in CT or MR scanners. [3]
A specific technology that offers potential benefit to reconstruction is found in MIT's publication by Kiani, B.T., et al. in 2020 titled "Quantum Medical Imaging Algorithms". The authors described prospective "exponential speedup over classical counterparts when data is input as a quantum state." [4]
In addition, benefit with reconstruction algorithms may be realized in emerging quantum hardware such as Ion Trap from IonQ, and a new CPU/GPU/QPU platform from NVIDIA. [5-6]
For Segmentation, 27 of the 191 FDA Approvals were identified that have been implemented for multi-modal applications. Quantum Inspired Neural Networks have been utilized in recent years that have had performance improvements over previous quantum results, yielding good Hippocampus segmentation. [7-8]
In addition, today's segmentation algorithms may see improvement through hybrid quantum neural networks that have ability to run larger data sets; Or require smaller training data sets to function, in specific cases. [9-13]
Quantum computing continues to improve regarding the number and quality of quantum bits. Regulatory organizations such as IEC and ISO look to close voting on quantum security standards, and will likely move to approve quantum technologies regarding new application areas, such as life sciences. [14-15]
References are available in the comments below. Have a productive rest of your day.
Smile at end!
3/3/23 "FDA Radiology Reconstruction and Segmentation Algorithms, Quantum Potential" References[1] https://www.fda.gov/medical-devices/software-medical-device-samd/artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices[2] https://www.chemicalqdevice.com/fda-aiml-approvals-basis-for-qnn-neuroimaging[3] https://www.chemicalqdevice.com/brain-disorders-and-quantum-computing[4] https://arxiv.org/abs/2004.02036[5] https://ionq.com/best-practices [6] https://developer.nvidia.com/qoda[7] https://link.springer.com/article/10.1007/s10489-021-03108-5 [8] https://link.springer.com/article/10.1007/s10489-021-02688-6[9] https://www.nature.com/articles/s41567-019-0648-8 [10] https://arxiv.org/abs/2210.09728 [11] https://arxiv.org/abs/2202.11204 [12] https://arxiv.org/abs/2301.08167 [13] https://www.nature.com/articles/s41467-022-32550-3[14] https://www.iso.org/standard/77097.html [15] https://www.iso.org/standard/77309.html
Created by Kevin Kawchak Founder CEO ChemicalQDevice2022 San Diego, CaliforniaAdvancing Neuroimaging