We Help Radiologists Stay Firmly in Control

Using machine learning image analysis, our Virtual Resident™ solution searches, measures, characterizes, and prepares a preliminary findings report. We leverage your existing workflow: use your familiar PACS and reporting system, while creating higher value reports faster.

Demands are Intensifying
The pressure on radiologists is intense—and escalating. More patients. More data generated with each study. Reimbursements going down.

RADLogics Virtual Resident
Your RADLogics Virtual Resident uses machine learning image analysis to process the enormous amount of imaging data associated with CTs, MRIs and X-rays. Within minutes, a draft report—with key images—flows into your reporting system. You can focus your time and attention on diagnosis, improving quality for your patients and institution, and collaborating with colleagues.

Machine-Learning Algorithms to Help You Achieve Better Diagnostics

Your Own Virtual-Resident™

AlphaPoint™ is like having a top resident preparing detailed information on findings for your review. Except that our Virtual-Resident uses machine-learning algorithms, and takes advantage of accessing, aggregating and analyzing data from thousands of factual clinical cases and applying that knowledge consistently — in seconds — to each case.

 

Radiologist Report Enhanced with Analytics

Alphapoint-Screen-Grab

Processing date and time: [11/18/2014 12:14PM]
Patient name: [067c13d] Patient sex: [Unknown]
Accession Number: [3154253] Patient Date of Birth: [6/6/2014]Technique:
[CT of the chest.
CT of the chest was performed following injection of iodinated contrast media.
Pathology:
[Pathology found]Findings:
[There is no evidence of pneumothorax.
There is no evidence of pleural effusion.

The ascending aorta has of borderline width, measuring 36.0 mm.The descending thoracic aorta width measures 23.0 mm.No consolidations or significant parenchymal opacities were detected.2 lung nodules were detected:Nodule #1 in slice #245Nodule #2 in slice #297

Please note: Pixel spacing in series measured as 0.82 mm; minimum nodule size reported is 4.9mm in all three dimensions (where minimum nodule size is 6 x pixel spacing)

Summary Report 1Summary Report 2Summary Report 3

Click on text links or CT scans for enlarged Key Images

 

Ready When You Are

Detailed, accurate findings for each case are available in a matter of minutes. By the time you sit down to review a case, the preliminary findings are up on the screen to assist you in performing the critical task of diagnostics and completing your report.

Everything in its Place

The findings are merged with the patient’s medical record information, and then flowed into your department or hospital’s form as a preliminary report. Every piece of information — patient identification, imaging technique, findings, including quantified measurements, and key images — show up where you expect to see it for your review and preparation of the final diagnostics report.

Comprehensive and Consistent Analysis

AlphaPoint uses automatic image analysis, and is not subject to human variability, minimizing the chance of inconsistencies.

Cloud Solution

The AlphaPoint cloud solution (US Patent 8,953,858, other patents pending) imports any DICOM-compatible study directly from the modality or the PACS. The software platform incorporates proprietary analytics, search, measurement, and other tools. All scans associated with a given study are combined into a single result. In a matter of minutes, AlphaPoint prepares detailed findings information that flows into any reporting, PACS, or HL7-compatible system for review by the radiologist.

AlphaPoint is a vendor- and modality-agnostic software analytics platform. It is currently available for CT scans. Future versions will support X-ray*, MRI* and ultrasound* scans.

AlphaPoint platform diagram

* Under development.

 

There’s an App for That!

The AlphaPoint platform supports an ever-expanding portfolio of scan modules, covering various modalities such as CT, XRay and MRI.

AlphaPoint uses an innovative App model. Each App was designed and developed in conjunction with leading radiologists, and was clinically validated in numerous clinical institutions.








FDA Clears RADLogics’ AlphaPoint Analytics Software

RADLogics’ AlphaPoint image analytics software platform, a system for the automatic analysis, review, and interchange of CT chest images, has been cleared for marketing by the U.S. Food and Drug Administration (FDA).