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http://blog.csdn.net/dgyuanshaofeng/article/details/88074036
The Solution
To aid the scan operator we developed a deep-learning (DL) based framework for intelligent MRI slice placement (ISP) for several commonly used brain landmarks. Our approach determines plane orientations automatically using only the standard clinical localizer images. This allows the scan operator to consistently get patient-specific slice orientations for multiple anatomical brain landmarks: anterior commissure-posterior commissure, orbitomeatal, entire visual pathway including multiple orientations through the orbits and optic nerve, pituitary, internal auditory canal, hippocampus, and circle of Willis (angiography).
Our method consists of three main steps (Figure 3):
- Image quality inspection: In the first step, we check if the given localizer image is suitable to identify the plane for the desired anatomy. This is achieved by using a fiver layer, dyadic reduction regular CNN classification network model (that we call “LocalizerIQ-Net”) to identify slices with relevant brain-anatomy, slices with artifacts and irrelevant slices. If the localizer image is not suitable for ISP, relevant feedback is provided to the scan operator. We used the built-in TensorFlow functions for image manipulation to achieve data augmentation during the training of LocalizerIQ-Net.
- Identification of anatomy coverage: Next, we locate the spatial-extent of the desired anatomy (brain) in the localizer images by incorporating a shape-based semantic image segmentation U-Net DL model (called “Coverage-Net”). This helps the next processing steps to be robust to changes in imaging parameter settings across hospitals and clinics as well as changes in shapes and sizes of the patient’s anatomy.
- Identification of precise plane orientation and location: For each desired anatomic structure (example, optic nerve), we find the scan-plane that is best suited to image that structure using one or more image segmentation 3D U-Net models (called “Orientation-Net”). Orientation-Net directly segments the desired-planes on localizer images, which is then used to compute the orientation and location.
[1] Intelligent Scanning Using Deep Learning for MRI [翻墙link] [百度网盘pdf，提取码：byg8]