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Deep Learning for Medical Image Analysis
Szöllösi, Albert ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This thesis offers possible solution to automatic 3D dental scan landmark localization. These scans are used in dental crown design and digital orthodontics to make the design process easier using specialized software. Before that, though, the scan has to be annotated for the software to know the positions of the teeth. The annotation process is done manually, which guarantees precision, but takes a lot of time. The result of this work could make said process much simpler by applying deep learning. Landmark localization was implemented using a convolutional neural network.
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Deep Learning for Medical Image Analysis
Szöllösi, Albert ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This thesis offers possible solution to automatic 3D dental scan landmark localization. These scans are used in dental crown design to make the design process easier using specialized software. Before that, though, the scan has to be annotated for the software to know the positions of the teeth. The annotation process is done manually, which guarantees precision, but takes a lot of time. The result of this work could make said process much simpler by applying deep learning. Landmark localization was implemented as heat map regression. Results of the regression were then used to comput the estimated landmark coordinates.
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Deep Learning for Medical Image Analysis
Szöllösi, Albert ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This thesis offers possible solution to automatic 3D dental scan landmark localization. These scans are used in dental crown design and digital orthodontics to make the design process easier using specialized software. Before that, though, the scan has to be annotated for the software to know the positions of the teeth. The annotation process is done manually, which guarantees precision, but takes a lot of time. The result of this work could make said process much simpler by applying deep learning. Landmark localization was implemented using a convolutional neural network.
|
|
|
Deep Learning for Medical Image Analysis
Szöllösi, Albert ; Kodym, Oldřich (referee) ; Španěl, Michal (advisor)
This thesis offers possible solution to automatic 3D dental scan landmark localization. These scans are used in dental crown design to make the design process easier using specialized software. Before that, though, the scan has to be annotated for the software to know the positions of the teeth. The annotation process is done manually, which guarantees precision, but takes a lot of time. The result of this work could make said process much simpler by applying deep learning. Landmark localization was implemented as heat map regression. Results of the regression were then used to comput the estimated landmark coordinates.
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