Radiology and medical imaging expands human vision and allows for more powerful diagnosis and treatment. EffectiveSoft combines the advances in medical science/ healthcare with the power of digital and information technology to enhance healthcare efficiency, quality, and value.
A radiology information system (RIS) is a software solution for managing medical images and other related data. It is used for resource management, reporting, results distribution, examination tracking, and procedures billing. A RIS often works together with a picture archiving and communication system (PACS) and a vendor-neutral archive (VNA).
Radiosurgery equipment requires highly sensitive software that is used for radiation therapeutic treatment for cancerous tissues. We offer workable custom radiology applications that complement radiosurgery devices and allow for radiation dose planning, radiation treatment, tumor location, and more.
EffectiveSoft provides medical imaging software, both desktop and mobile, for qualitative analysis and visualization of any biomedical images. Our custom medical imaging applications support grayscale, color and 3D images in various file formats.
With the help of AI technologies such as machine learning and computer vision, health risks can be identified early on. We build AI-powered solutions that expand the field of radiology. By quickly scan and analyze the accumulated patient data, thus reducing the number of errors in interpreting images and making a positive impact on the lives of people.
Medical images (quality or precision) rely on a wide range of different compression standards, many of which are complex and continue to evolve. Maintaining and verifying compliance with these standards is no easy job. At EffectiveSoft, we provide our software support services for all sorts of medical image formats.
Image compression, decompression and processing can place heavy demands on processors, especially when processing a large number of mages on servers. EffectiveSoft builds software that maximizes the speed of medical image processing and therefore improves diagnosis and treatment.
We do our best to enhance the quality of medical images in order to reduce noise, eliminate artifacts, compensate for spatial overlaps, and increase contrast. With improved images, healthcare professionals can give a correct diagnosis and administer follow-up treatment as well as ensure automatic image analysis in the future.