However, conventional CNN is a complex architecture and the time to process the image, large data requirement and overfitting are some of its challenges. This study proposes a transfer learning approach using InceptionV3 to classify brain age from the MRI images in order to improve the brain age...
This labeling process simulates the iterative process that we ourselves use to locate structures in images. We demonstrate its application in three data sets, labeling brain MRI by locating the longitudinal and lateral fissures and the central sulci and then determining boundaries for the frontal ...
Appropriate images extracted from the MRI of mothers' wombs can be of great help in the medical diagnosis of fetal abnormalities. As maternal tissue may appear in such images, affecting visualization of myelination of the fetal brain, it is not possible to use methods routinely used for ...
MRI images help physicians study and diagnose diseases or tumors present in the brain. This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis. The ambiguity of Magnetic Resonance (MR) image features is solved in a simpler manner. The MRI ...
however, that it's not all encompassing. It's a great book for a first year resident to read to get the basics down, after that you'll want to move on to something that has a lot more details. However, great ...
The potential for early detection of Alzheimer's disease might be achieved by the use of Magnetic Resonance Imaging (MRI). However, the MRI dataset has an issue in class imbalance problem. To address the problems in the dataset, a data balancing technique called SMOTETomek is used and then ...
study to measure different aspects linked to motor activity when they press buttons, in order to see if the button pressing was related to brain activity measured over the motor cortex. To increase the veracity of the aim, electrodes were also placed on their fingers and connected to a real ...
Aim: To compare attenuation correction (AC) approaches for positron emission tomography/magnetic resonance imaging (PET/MRI) in clinical neuro-oncology. Methods: Forty-nine PET/MRI brain scans were included: brain tumor studies using (18)F-FET (n = 31) and 68-Ga-DOTANOC (n = 7) and stud...
Conclusions: The GAN model we developed produced highly accurate synthetic CT images from conventional, single-sequence MRI images in seconds. Our proposed method has strong potential to perform well in a clinical workflow for MRI-only brain treatment planning. 展开 ...
Prices may be subject to local taxes which are calculated during checkout Additional access options: Log in Learn about institutional subscriptions Read our FAQs Contact customer support References Cherry, S.R.In vivomolecular and genomic imaging: new challenges for imaging physics.Phys. Med. Biol....