64 citations · 127 across the 14 of their papers we have counts for
5 papers · 1 filter
A hierarchical approach for pulmonary nodules identification from CT images using YOLO v5s nodule detection and 3D neural network classifier
Yashar Ahmadyar Razlighi, Alireza Kamali-Asl, Hossein Arabi
In the first step, a pre-trained model (YOLO) was used to detect all suspicious nod-ules. The YOLO model was re-trained using 397 CT images to detect the entire nodule in CT images…
Deep Learning-Based Partial Volume Correction in Standard and Low-Dose PET-CT Imaging
Mohammad-Saber Azimi, Alireza Kamali-Asl, Mohammad-Reza Ay +2
A standard dose of radioactive tracer must be delivered into the patients body to obtain high-quality Positron Emission Tomography (PET) images for diagnostic purposes, which raise…
Design and implementation of brain surgery bipolar electrocautery simulator using haptic technology
Reza Karimzadeh, Javad Sheikh, Hamed Azarnoush +1
Surgical simulators have been widely used in training and evaluation of physicians and surgeons. Virtual reality augmented with haptic technology has made it feasible to develop mo…
Joint brain tumor segmentation from multi MR sequences through a deep convolutional neural network
Farzaneh Dehghani, Alireza Karimian, Hossein Arabi
Brain tumor segmentation is highly contributive in diagnosing and treatment planning. The manual brain tumor delineation is a time-consuming and tedious task and varies depending o…
Does prior knowledge in the form of multiple low-dose PET images (at different dose levels) improve standard-dose PET prediction?
Behnoush Sanaei, Reza Faghihi, Hossein Arabi
Reducing the injected dose would result in quality degradation and loss of information in PET imaging. To address this issue, deep learning methods have been introduced to predict…