DisQ-HNet: A Disentangled Quantized Half-UNet for Interpretable Multimodal Image Synthesis Applications to Tau-PET Synthesis from T1 and FLAIR MRI | ScienceToStartup | ScienceToStartup

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References (47)

[1]

2024 Alzheimer's disease facts and figures

2024

[2]

Deep learning based synthesis of MRI, CT and PET: Review and analysis

2023Sanuwani Dayarathna, Kh Tohidul Islam et al.

[3]

A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles

Founder's Pitch

"DisQ-HNet is a framework for synthesizing tau-PET images from MRI data to support Alzheimer's diagnostics with interpretability."

Medical AI•Score: 2•View PDF ↗

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DisQ-HNet: A Disentangled Quantized Half-UNet for Interpretable Multimodal Image Synthesis Applications to Tau-PET Synthesis from T1 and FLAIR MRI

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Founder's Pitch

"DisQ-HNet is a framework for synthesizing tau-PET images from MRI data to support Alzheimer's diagnostics with interpretability."

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DisQ-HNet: A Disentangled Quantized Half-UNet for Interpretable Multimodal Image Synthesis Applications to Tau-PET Synthesis from T1 and FLAIR MRI

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References (47)

Founder's Pitch

"DisQ-HNet is a framework for synthesizing tau-PET images from MRI data to support Alzheimer's diagnostics with interpretability."

Commercial Viability Breakdown

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