Developing new CEST-based tools for more accurate and reliable cancer diagnosis
CEST imaging principles are quite simple and involve chemical species which contain in their structure a hydrogen proton that can be exchanged with those of water. By applying a radiofrequency (RF) pulse at their resonance frequencies, the chemical species of interest – such as amide or hydroxyl groups - reach a saturation state; at this point, their labile excited protons are exchanged with the non-excited protons of the water.
If this process is continually repeated through few seconds of RF irradiation, it leads to a buildup of saturation in water. In this way, the concentration of the targeted species can be indirectly measured by the decrease of water signal, easily detected by the classic MR imaging sequences.
Read our CEST imaging brief in the latest issue of Olea Imagein
ISMRM : Save the date for our symposium
During the ISMRM 27th Annual Meeting & Exhibition, we invite you to attend our symposium: “CEST Imaging: Promising Horizons in Clinical Practice”.
Save the date: Tuesday May 14th at 6.00 pm, room 518A-C, Montreal, Palais des congrès.
More information, here.
This brand new App is meant to automate and simplify breast MR sreening. Our multi-vendor solution allows an easier and standardized morphological series review, the subtract series are automatically computed and displayed, as well as thin and thick MIP MPR series. Automated kinetic maps computation allows to automatically identify suspect tissue. The user has access in one click to various metrics: volume, maximum diameter, distance to skin, to chest and to nipple.
Texture Analysis makes it possible to use data that is invisible to the human eye at the marcoscopic level and to asses, for example, the heterogenity of a lesion. It is usable for all anatomies and imaging modalities (MRI, CT-Scan, PET-CT Scan, and PET MRI-Scan) and thus opens the way for AI and Radiomics.
Precise, efficient & reproducible Knee MRI Segmentation
Our Cartilage Segmentation plug-in off ers a fully automated solution to quickly and eff iciently segment knee cartilage to characterize potential tissue degeneration.
This new plug-in is fully embedded within our platform and works seamlessly with Olea Sphere® plug-ins.
Using T1 MR imaging, this application provides detailed and intuitive views of knee cartilage integrity and patient anatomy.
Read the Interviews with MS Ashley Williams and MD Mario Padron in our 4th Edition of Olea Imagein.
• 3D cartilage thickness rendering
• Automatic knee cartilage segmentation
• Segmentation of bones and cartilage surfaces
- Femur cartilage and bone
- Tibia cartilage and bone
- Patella cartilage and bone
• Viewer: load conventional series, T2 mapping, …
• Integrated within Olea Sphere®v3.0
• Intuitive environment
More information, here.
Develop your own post-processing applications
Thanks to our brand-new Software Development Kit (SDK), you can integrate your research whatever the language used (Java, Python, C, C++, MatLab, and more). Along our cutting-edge framework, we offer a starter kit with essential components
(UI & algorithms), already used and validated in Olea Medical’s various solutions. Therefore, using these existing libraries and focusing only on integrating your algorithms you will quickly have a testable and deployable application. Dicom reader, advanced post-processing algorithms, batch processing, viewer,
measurement and volume tools are some of the main available features on this unique platform.