Technical FAQs

Having the right technology in place is essential for healthcare organizations seeking to deliver better patient outcomes. That’s why medical technology developers are working hard to build the next generation of software tools that will help medical professionals to deliver care more effectively. 

Annotation features provide a number of benefits in these ongoing efforts. Although typically associated with editing and workplace collaboration, medical annotations also have a very different and very specific role when it comes to diagnostic imaging and patient health records.

Enhancing Healthcare Collaboration with Annotations

One of the most straightforward use cases for medical annotation is communicating important information regarding diagnostic images. As images like MRIs and X-rays are passed back and forth between providers, radiologists, technicians, and clinicians, the ability to add comments and point out important details greatly reduces the chance of confusion or of some critical detail being overlooked.

The challenge in these cases, however, is to annotate images and documents without altering the integrity of the original files. This requires healthcare technology developers to build solutions that can retain an unaltered version of the file even as multiple collaborators view and make comments. 

Medical Annotation and Machine Learning

Healthcare solutions are rapidly incorporating sophisticated machine learning tools to analyze large quantities of data and make a quick, accurate diagnosis of conditions. Before these powerful tools can perform that diagnostic work, they need to be properly trained to know what they’re looking for, especially when it comes to very nuanced differences between scanned images and seemingly unrelated details in patient records.

By using annotation tools, medical technology specialists can provide excellent guidance for machine learning development. An MRI scan, for instance, contains so much information that an AI-driven program isn’t going to know what to look for unless the key elements are called out with annotations that indicate certain parts of the image or provide comments about noteworthy aspects.

The DICOM Dilemma

While many software integrations allow developers to incorporate annotation tools for common file formats like PDF and JPEG, the healthcare sector presents a unique challenge in the form of DICOM files. This industry-specific format contains both images and important metadata identifiers that provide information about the image itself and the patient in question. While there are ways to extract images from DICOM files and convert them into a more manageable format, doing so could endanger compliance status or permanently degrade the image quality.

Developers working on healthcare technology solutions need to make sure they can not only deliver annotation tools, but also the ability to add annotations to DICOM files without altering the source file itself. 

Mastering Medical Annotation with ImageGear Medical

ImageGear Medical provides a broad range of XML-based annotation features that allows healthcare software developers to implement UI elements for marking up both images and documents. Since this powerful imaging SDK also gives users the ability to create and view DICOM files, it can quickly enhance the functionality of medical applications to enhance collaboration and ensure diagnostic accuracy.

Once integrated into an application with a viewing UI, ImageGear Medical supports several commonly-utilized annotation marks that makes it easy for users to highlight certain aspects of an image, comment on them, and even cover up some elements using filled-in graphical objects. Annotations can also be grouped in layers to make them easier to manage and distinguish from one another.

ImageGear Medical annotation objects for DICOM include:

• Text: Adds descriptive text using a variety of fonts, colors, and sizes. Opacity can be adjusted and the text object can appear with or without a border.
• Point: Places a coordinate point on the image or document, which can be used to support other annotation marks.
• Polyline: A series of connected straight lines formed by dragging and clicking a mouse or pointer.
• Curve: Used for creating spline curve marks. Users can select multiple vertices and tensions when creating curves.
• Ellipse: A circular outline mark that can be used to indicate important elements of an image or document. When filled, it can also cover up areas of the image.
• Polygon: Like the ellipse, it can be filled or unfilled and is typically deployed to cover or highlight some aspect of an image or document. Polygons are especially useful for medical annotation because they can capture more lines and angles than simple rectangles or circles.

In order to maintain the integrity of the original image, ImageGear Medical stores annotations as a separate file that is overlaid upon the image during display. While annotations can be merged, or “burned in” the file, keeping them separate ensures that the original image itself is not altered directly. This is incredibly important when it comes to DICOM files, which often need to be kept on file for baseline comparisons on a future diagnosis.

Enhance Healthcare Flexibility with ImageGear Medical

Annotations and DICOM viewing support are just the beginning of ImageGear Medical’s expansive feature set. It also provides advanced filtering tools for sharpening and smoothing as well as image cleanup functions like despeckling, noise removal, and deskewing. With support for several dozen medical image and document formats, ImageGear Medical can easily convert files into easy-to-manage formats and compress files for efficient storage.

Available for .NET and C/C++ environments, ImageGear Medical can turn your healthcare application into a powerful annotation platform with full support for DICOM files. Start your free trial of this powerful SDK to discover first-hand how it can empower your medical annotation solution.

Forms have long been used to provide organizations with important information about their customers. For a financial services or insurance company, that information might be used to determine eligibility for a loan or set a policy rate. Legal teams and healthcare providers, on the other hand, often use them to quickly gather information that could be relevant to a client’s case or a patient’s care. By building form workflow automation into their applications, developers can provide these organizations with the tools they need to improve efficiency and provide better service to their customers.

A Better Way to Capture Data with Form Workflow Automation

At its core, a forms workflow is designed to capture data from completed forms and route that information to the appropriate destination. That end point will vary based on the application. In some cases it could be used to autopopulate database entries. Other systems may feed it into machine learning algorithms to identify trends or provide predictive insights. Before any of that can happen, however, automated workflows with forms recognition capabilities need to be in place to identify various form types and extract information from them using various forms of optical recognition.

The primary benefits of workflow automation are speed and accuracy. By building a forms workflow within their applications, developers can help their customers process submitted forms much more efficiently than they could by hand. Even if manual data entry wasn’t so prone to human error, it would still be a waste of valuable resources to have skilled employees performing such a repetitive, routine task. Automating this sort of work is often the first step in maximizing performance in other areas of an organization because it frees up resources that can be directed toward higher-value tasks.

Say Goodbye To Paper (Mostly)

Organizations have talked about going “paperless” for decades, but they frequently find it much more difficult to do so in practice. That’s largely because physical forms continue to be used across many industries. Converting these paper forms into digital format as quickly as possible is critically important. Without some way of incorporating them into an automated workflow, inefficiencies and manual errors will continue to creep back into business processes. 

A forms workflow needs to be able to handle scanned forms images in addition to purely digital documents. Robust forms identification tools are essential for this process because they have the ability to match any submitted form to a library of predefined templates. Without identification capabilities, applications would need to be given specific information about every form. At best, submitted forms would need to be manually presorted before they could be scanned and uploaded for processing rather than being converted into digital format all at once and identified automatically.

Recognition and Extraction

Once forms are scanned, uploaded, and identified into an application, the data capture process can begin. While digital forms can easily send information contained in fields to the proper destination, a scanned form is just a static document image. Even if the form was filled out digitally and never existed as a paper document, the fields may not be responsive or the entire form may be nothing more than a flattened PDF image. In these cases, the only way to reliably capture data is to implement some type of optical recognition.

Optical Character Recognition

For machine printed text, forms workflows can deploy Optical Character Recognition (OCR) to identify and extract information from an identified form. High-quality OCR engines can read multiple languages, allowing them to capture data from almost any source and send it to the next phase of an automated workflow. When extracting text, OCR tools can be set to carry out full-page extraction, which pulls text from the entire form, or zonal extraction, which focuses the data capture effort on a smaller, predetermined area. The latter approach is much more common with forms processing because it allows the application to set parameters on each zone to enhance performance. If the OCR engine is instructed to look for only numbers in one field and specific regular expressions in another, it will be able to identify and extract text faster and more accurately.

Intelligent Character Recognition

Of course, many physical forms submitted for processing will not be filled out with standardized digital fonts, but rather by hand using a pen or pencil. For these handwritten forms, Intelligent Character Recognition (ICR) will need to be deployed to read and extract field contents. Although identifying handwritten text is a much more challenging undertaking, the combination of a powerful ICR engine and good form design can greatly improve accuracy and processing times to keep information moving through automated workflows.

Optical Mark Recognition

Forms frequently use checkboxes or fillable bubbles to indicate important information. When scanned images are run through a forms workflow for processing, applications need to be able to quickly identify the presence of a mark and apply the conditional information associated with it. Today’s forms workflow tools utilize Optical Mark Recognition (OMR) to detect the presence or absence of marks automatically. They can also check the entire form to determine what information might be missing, such as essential fields or signatures.

Unlock Your Form Workflow Automation Potential with the FormSuite Collection

Building an automated workflow for forms processing requires a variety of software tools and specialized imaging expertise. It’s a challenging task that becomes even more difficult when developers are facing tight deadlines for other application features. With the right forms workflow SDKs, software teams can rapidly integrate the features needed to identify a variety of forms and capture vital data using full-page or zonal text recognition.

Accusoft’s Forms Collection bundles our powerful forms toolkits into a single, easily deployed package. Whether you’re using FormFix to identify and align forms, cleaning up scanned images for better recognition results with ScanFix Xpress, or deploying fast, accurate OCR and ICR with SmartZone, FormSuite provides all the SDK resources your team needs to unlock your application’s workflow automation potential. Learn more about what’s included with the FormSuite Collection by downloading our detailed fact sheet.

Automated data capture tools are an essential feature of today’s business applications. Without the ability to quickly extract information from incoming forms and documents, organizations will struggle to keep their records, databases, and customer-facing software up-to-date. While software SDKs like Accusoft’s SmartZone can deliver powerful optical character recognition (OCR) and intelligent character recognition (ICR) to help applications accurately capture the information they need, these tools were not designed to operate in isolation. To get the best performance out of them, they need to be incorporated into a comprehensive and well-designed forms processing workflow.

Building an Efficient and Effective Forms Processing Workflow

Although data capture is often the primary objective of forms processing, a number of elements need to be in place for an application to be able to deploy SmartZone’s powerful OCR/ICR functionality. The first step involves the creation of form templates that can be used both for identifying incoming scanned forms and for defining field regions on the page from which data can be extracted. Building this library of templates provides a road map of sorts for the recognition process.

After form images are acquired, either from pre-existing digital documents or newly scanned images, they may need to be enhanced or cleaned up to ensure the best recognition results. Operations such as binarization, despeckling, deskewing, and line removal can all improve the data capture process, especially in the case of scanned documents. Older documents frequently include a great deal of image noise when scanned into digital format, which can make it difficult for an OCR/ICR engine to properly segment and read characters cleanly.

Once a form image has undergone enhancement, it can be matched and aligned with the correct template to ensure that the SmartZone recognition engine will be able to obtain a clean field clip. Scanned images can be overlaid via an alignment algorithm that performs minor adjustments to match it exactly with the correct template. This step is crucial because the data capture process is set up to read the field areas identified by the template rather than recalibrating for each form. If the alignment is off, the engine will not get a clean read of the characters, which could result in inaccurate recognition results.

After the form is identified and aligned, additional enhancement and cleanup operations can be performed on the specific areas of the form that contain information to be extracted. This typically means individual field areas where text or other characters have been entered. The locations to be cleaned up can be designated during the template creation process when data extraction zones are defined. In some instances, a processing workflow may skip the initial full-page enhancement and instead only perform clean-up on areas where data capture will be carried out. This approach is often more efficient from a processing standpoint, especially when targeted, zonal recognition is being applied.

Form image dropout can also be performed at this stage, which involves the removal of image content like signature lines, text field boxes, comb lines, or other extraneous guiding content. Here again, proper form alignment is crucial. If the form is slightly “off” from the template, valuable character content could be removed, making accurate recognition much more difficult. Good form dropout tools should also be able to reconstruct characters that lose pixel data during the dropout process, which is common for characters that have an element that overlaps form lines (such as the lower half of a “j” or a “y,” which might otherwise be read as an “i” or a “v” if not repaired prior to recognition).

SmartZone’s Role in the Recognition Phase of Application Workflows

After a form is acquired, enhanced, identified, and aligned, it can be passed along to the next stage of the workflow for text recognition using SmartZone OCR/ICR. There are a few options that can be selected at this point to help improve recognition accuracy and faster data capture performance.

1. Select Character Sets

SmartZone supports a wide variety of languages and alphanumeric character sets. Realistically, only a few of these sets will need to be used at any one time. Selecting only the sets needed for a particular form will improve recognition accuracy and speed. For instance, there’s no need to have support of Cyrillic languages (like Russian or Greek) enabled if all of the forms being processed are in English.

2. Designate Field Types

SmartZone can designate the expected format of text found in specific fields on a template. Rather than reading each field out of context and extracting the contents without knowing whether or not it’s been filled in correctly, field types can be set to values such as date, email, currency, phone number, or Social Security Number. Regular expressions can also be established for more customizable results. If the character content of the field doesn’t match the designated field type, SmartZone will immediately return an exception and move on rather than trying to recognize and extract the incorrect data. Setting this parameter can greatly improve both accuracy and speed.

3. Set Minimum Character Confidence

Every character SmartZone reads is assigned a confidence value, which reflects the OCR/ICR engine’s assessment of its recognition accuracy. A lower value means that there is a higher likelihood that a character was incorrectly identified. Setting a minimum character confidence value ensures that any character result below that value will be rejected and replaced with a designated rejection character. In practice, this control is used to determine which characters require a manual review following recognition. Setting a high confidence value will ensure higher recognition accuracy, but will likely lead to more exceptions that need to be reviewed by a human.

SmartZone Recognition Results

After character recognition is performed, results can be returned for the character, text line, or text block level. This data can then be passed along to the next stage of a business workflow or used to populate databases connected to the application. Operation instructions, identification, and image areas defined can be transferred to other components for additional forms processing or stored in memory for later access using SmartZone’s Read From Stream or Write From Stream functions.

Getting Started with SmartZone

With support for both OCR and ICR data capture, Accusoft’s SmartZone SDK can serve a vital role in high-performance forms processing applications. The powerful OCR engine can recognize multiple languages, including select Asian, African, and Indian characters. Capable of performing full page or zonal text extraction, SmartZone also includes a variety of customization features that can improve accuracy and recognition speed. Learn more about this versatile SDK’s features and use cases in our product fact sheet.

When President Joe Biden signed the $1.9 trillion American Rescue Plan Act relief package into law on March 11, 2021, millions of Americans looked forward to receiving a much-needed $1400 stimulus check from the government. Although many people would receive paper checks directly from the Internal Revenue Service (IRS), anyone who had previously filed their taxes electronically and had returns delivered to their bank accounts were eligible to receive their stimulus relief via direct deposit. The IRS set the date of March 17 for the delivery of stimulus funds, which would give sufficient time for payments to make their way through the complex Automated Clearing House (ACH) system used to transfer payments electronically.

FinTech Lenders to the Rescue

But on March 12, just one day after the landmark bill was signed into law, many FinTech banking customers received notifications that funds had already been delivered to their accounts. The digital banking startup Current bragged on Twitter that afternoon that it had already distributed $600 million to 250,000 customers. On March 15, the FinTech lender Chime announced that it had paid about $3.5 billion to more than one million customers over the weekend. Chime had previously made headlines the previous spring when it advanced stimulus funds from the CARES Act to customers before the government actually made the money available.

Unsurprisingly, the announcements caused quite an uproar from customers at traditional banks that did not start releasing funds until the previously announced March 17 date. Despite many of the accusations leveled at these lenders, however, the discrepancy had nothing to do with banks deliberately withholding funds and everything to do with the unique business model of leading FinTech lenders.

In the case of Chime, for instance, the company frequently makes payment funds available to customers as soon as the transfer is initiated, rather than waiting for it to clear through the ACH. “I guess you could argue we’re taking a risk,” said Chime co-founder and CEO Chris Britt. “But we’ve been told by the Federal Reserve that the money is coming so we don’t think it’s that much of a risk.” 

Traditional banks were quick to respond by saying that they could not make funds available before March 17 because that was the date set by the government for the money to actually be transferred. For FinTech companies with higher risk tolerance, the delay provided a unique opportunity to demonstrate the benefits of digital lending applications. During the first wave of stimulus checks in April of 2020, mobile banking app registrations increased by 200% over the previous month as Americans rushed to embrace various forms of digital banking.

The Flexible Features of FinTech Applications

Part of the reason why FinTech lenders are willing to offer more generous services to customers is that they often assess risk differently than traditional banks. Armed with sophisticated algorithms and data capture tools, FinTech applications are able to gather more information about customers and lending sources to create a more accurate risk profile.

Over the last two decades, FinTech developers have worked hard to build the digital platforms that innovative firms are using to offer these services. These software solutions need to be flexible enough to process information quickly and provide essential functionality that helps both FinTech firms and their customers to view and share information quickly and easily.

Forms Processing

Structured forms are an essential tool of the financial services industry, whether it’s a loan application or an IRS tax form. The faster those forms can be processed, the more quickly firms can deliver money into the hands of their customers. That’s why FinTech developers need to make sure they’re incorporating the forms processing tools that make it easy to automate data capture. Given that the latest round of COVID stimulus funds are based upon tax return information, many customers will be scrambling to update their records as quickly as possible. By integrating the tools to process that data with haste, FinTech developers can help firms keep pace with the needs of their clients.

Easy Viewing

While FinTech developers are primarily building applications for lenders, they should always keep in mind that a solution that doesn’t provide a positive customer experience will have trouble catching on in a crowded marketplace. Today’s banking customers expect transparent and intuitive applications that allow them to quickly view their financial records and check the status of applications or loans. By building HTML5 viewing capabilities into their FinTech solutions, developers can help customers track the status and history of their finances, which is certainly a major concern as they monitor the status of their stimulus payments.

Interactive Tools

With all of the nuances surrounding COVID stimulus payments in the latest round of legislation, many customers will be turning to their FinTech lender to understand how much money they can expect to receive based on their eligibility. A well-designed spreadsheet may be able to provide this or similar information much more quickly than building a dedicated tool within an application, but downloading XLSX files can be a hassle for many people, especially for customers who primarily interact with their FinTech bank using a mobile device. By giving firms the ability to securely embed spreadsheets into their applications, developers can help them to quickly share tools and resources with customers, regardless of what kind of device they’re using.

Empowering the FinTech Future with Accusoft

Accusoft’s collection of SDK and API integrations allow FinTech developers to build a broad range of features into their applications to streamline processing and accelerate vital financial services. 

Our FormSuite forms SDK collection can automate form identification and OCR data capture to help FinTech applications maintain their speed advantage when it comes to processing applications and loans. For financial platforms that need comprehensive viewing functionality, PrizmDoc Viewer’s HTML5 viewing, annotation, and redaction capabilities can turn any platform into a powerful document viewer that helps users handle most of their financial business purely through their FinTech application. 

And when it comes to embedding interactive spreadsheets to provide quick reference and calculations for various services, PrizmDoc Cells allows developers to bypass the difficult work of building that functionality from the ground up. To learn more about how Accusoft integrations are powering the next generation of FinTech applications, visit our financial services page and download our FinTech integrations fact sheet.