The polymerase chain reaction (PCR) technique is widely used to rapidly make millions to billions of copies of a specific RNA/DNA sample. Read about proof of concept.
We developed an AI algorithms for the segmentation of thoracic aorta on contrast enhanced cardiac CT images.
Graylight Imaging specialists focused on developing of an algorithm for pelvis bone classification and segmentation. Using U-net-like architecture, we distinguish the pelvic bones and their fractures.
Improving lung cancer diagnosis from medical image data is a key factor of the screening process. We conducted a study using radiomic features elaborated from the image which could correlate with patient’s clinical parameters.
We designed a convolutional neural network (CNN) architecture (with just two convolutional layers and a fully-connected classifier) operating on 3D patches, capturing several neighboring frames from of an input CT image frame.
We created an iterative algorithm resistant to most problems experienced in practice in precise geometry preparation for 3D Print.
Blender plugin we created for inspecting coronary vessels in MPR and CPR views that facilitates the segmentation from CT significantly.
Check our project where we created algorithms for precise segmentation of the coronary arteries on computed tomography images.
Read about the project in which we worked on the Post-Operative Delirium and Post-Operative Cognitive Dysfunction prediction model.
We’ve created a precise algorithm that performs automatic brain tumor segmentation with subregions and volume calculation.
We conducted the experimental study to create and train ML for automated segmentation of pediatric optic pathway gliomas (OPG).
Read about the project in which we created an AI model dedicated to advanced segmentation of postoperative glioma.
Read about the project in which we created an AI model dedicated to advanced segmentation of preoperative glioma.