One of the fastest-growing healthcare fields is medical imaging. In recent decades, it has expanded to encompass CT scans, MRIs, ultrasound, and nuclear medicine. Along with medical imaging gear and systems, software that handles these pictures has advanced greatly.
The DICOM standard (Digital Imaging and Communications in Medicine) has improved medical picture quality. Medical pictures must be acquired, stored, retrieved, and shared in DICOM format.
Every hospital requires a DICOM workstation. The PACS (Picture Archiving and Communications System) virtual holding space for digital DICOM pictures has simplified storage and retrieval.
Medical imaging software for viewing DICOM pictures is abundant. Free and paid medical imaging software may have more sophisticated capabilities. Radiologists are getting used to the latest medical imaging software for viewing and storing images, so manufacturers are looking for new ways to solve problems in other areas of the imaging workflow.
Software for Medical Image Analysis
Medical image analysis software ‘analyzes’ medical imaging data. Analysis may improve diagnosis, compare photos of the same patient at various times to detect disease progression, and estimate prognosis.
Along with imaging technological advances, medical imaging software is improving its analytic capacity to independently identify clinical irregularities in medical pictures.
Why is medical image analysis software needed?
Medical image analysis is generally a cognitive function of the radiologist or physician. With medical improvements, patient scan requests have increased. More pictures need to be examined since medical scan outputs are more detailed and include several portions.
Radiologist interpretation of so many pictures is time-consuming, difficult, and highly specialized. Over time, radiologists' workload has increased, while the number of qualified professionals has only grown by half — leading to a significant human resource deficit in the radiology field.
Machines have the potential to alleviate this issue by evaluating medical images and identifying abnormalities.
One way to achieve this is through advancements in medical image analysis software development. Such software uses deep learning techniques to read and analyze large volumes of images simultaneously, drastically reducing the burden on radiologists.
By flagging suspicious images for closer inspection, the software helps medical professionals focus on the most urgent cases, ultimately improving diagnostic efficiency and patient outcomes.
What medical image analysis software is available?
Aidoc: Tel Aviv-based Aidoc develops medical image processing software for full-body CT scan diagnosis. The software detects high-level visual anomalies in head, neck, chest, and abdominal CT images. The company's case study showed that Aidoc considerably decreased report turnaround time, especially for head and neck scans.
Arterys, situated in San Francisco, uses cloud computing and deep learning AI algorithms. Medical image analysis software improves speed and accuracy. Arterys first created applications for cardiac MRIs but also helped detect abnormal lesions in liver, lung, and mammography.
What are medical image analysis software limitations?
The computer algorithms behind medical image analysis tools determine their quality. A computer cannot think or see, yet it produces numbers and algorithms.
Thus, its algorithms determine its output. Since the technology is new, there is space for mistakes. Medical imaging analysis software may minimize radiologists efforts, but it cannot yet replace them. It is less popular than medical image processing software since it is relatively young.
Medical Image Processing Software
Medical image processing software alters captured pictures. Some organizations call medical image processing software medical image analysis software, however, it doesn't analyze pictures. Processing simplifies manual analysis for the radiologist. Medical image processing includes segmentation, registration, and visualization.
Segmenting Images
Segmentation involves separating a picture into separate pieces. These portions should illustrate various structures or organs to be significant.
Functions of medical image segmentation software include:
The program's area of interest may contain tumors, nodules, and other diseases.
Anatomical boundaries: Segmentation software can detect blood vessel borders.
Volume measurement: Medical image segmentation software can compute tumor and anatomical cavity volumes. Monitoring tumor size while on therapy is helpful.
Register Image
Image registration aligns pictures properly. The computer learns a succession of ‘target’ pictures in this method. When the computer receives a new source' picture, it alters it to match the target. Transformation models, similarity functions, and optimization may register images.
Medical image processing software image registration applications:
Image fusion allows us to combine medical picture data from various sources into a single dataset. This is very helpful for understanding anatomy-functional relationships. CT scans reveal structure, whereas PET scans reveal metabolism. One dataset may include both types of data via image fusion.
Comparing photos over time: Image registration can compare images throughout time. This helps measure cardiac movement and respiratory function changes throughout the MRI session. It may be used to track illness development over many years.
Analyzing anatomy: Image registration may compare photos from various persons in a population. This may describe population anatomy.
Image registration enables computer-assisted surgery. Using a preoperative CT scan or MRI picture during surgery allows image-guided surgery.
Visualizing Images
Medical image visualization software alters dataset viewing. This facilitates multi-perspective examination. Visualization involves studying data, altering it if necessary, and visualizing it more clearly than the original dataset. Several post-processing methods enable medical picture viewing.
Imaging applications using medical image processing software:
3D reconstruction: Medical image processing software usually includes 3D reconstruction tools. 3D reconstruction combines all dataset portions into one picture. Operators can quickly evaluate anomalies because of greater anatomical orientation than slices. 3D medical imaging software identifies abnormalities more quickly. If necessary, 2D visualization may provide more information.
2D visualization: The reverse of 3D reconstruction. It may show the original imaging data from 3D or 4D reconstructions or multiple dataset portions. 2D visualization includes multiplanar reformatting, which creates new sections from 3D and 4D reconstructions at various planes. MPR scans curvilinear structures like the spinal canal and blood arteries. Most 3D medical imaging software supports MPR.
Medical Image Management Software
As the number of patients receiving diagnostic medical imaging increases and the quality of medical pictures improves, healthcare facilities and hospitals must manage vast datasets.
This massive imaging data might be difficult to store, retrieve, and handle. The organization and integration of such datasets via medical image management software simplifies this procedure.
PACS servers may be coupled with DICOM workstations in medical image management software. Standard medical picture management software should include:
Replaces physical archiving with controlled digital storage of medical picture databases.
Radiologists may obtain medical imaging data from anywhere and examine it on numerous platforms at once.
Allows picture export to different file formats for teaching, learning, and publishing/website usage.
Medical picture data may be integrated with patient data in electronic health records, health information systems, and radiology information systems.
Innovative contributions by Darly Solutions play a pivotal role in streamlining the integration of imaging data with electronic health records and other healthcare systems, ultimately enhancing diagnostic workflows.
Why is medical image dosage tracking software needed?
With the growth of CT-guided diagnosis and intervention, including nuclear medicine scans and angiography, patient and physician radiation exposure has increased. Legislators require patients to monitor their radiation exposure and document it in their health records. Doctors' radiation exposure must also be tracked