Description:Field of the Invention
Vein Visualization in health care is used to visualize the veins, making it easier for health care professionals to locate veins. Locating the veins using a vein visualizer is one of the first practical uses of augmented reality in the medical field.
Objective of the Invention
It is very important to draw blood to diagnose the problem in the medical field. The irony is many people are frightened of needles. In many cases, it is not possible to find veins at first attempt and it is a discomfort for many patients. So, visualization makes it easy to find veins at the first attempt. Hence it helps healthcare professionals as well as patients by reducing stress and pain. It is used not only to find veins but also to avoid them during aesthetic procedures. Vein visualization can be vastly used in the medical field.
Background of the Invention
Vein visualizers, often referred to as vein finders or vein illuminators were created, which was a huge advancement in the medical industry. These tools are made to help medical practitioners find veins for actions like venipuncture (blood collection) or intravenous (iv) catheter placement.
Researchers started looking into using near-infrared (NIR) light to improve vein imaging in the 1900s. Veins can be seen as dark lines on the skin when NIR light penetrates the skin and interacts with hemoglobin in the blood. Vein visualizers were built on the principles of this idea.
One significant development occurred in 2005 with the launch of christie medical holdings, inc.'s vein viewer, the first commercially available vein visualization equipment. the vein viewer used NIR light to project an image of the veins onto the patient's skin in real time. this technology became well-liked in hospitals and clinics because it significantly increased vein visualization.
Many businesses and researchers have entered the space, continually advancing and advancing visualization technologies. while some improvements intended to make the vein, images obtained clearer and more detailed, others aimed to make the devices easier to use and more portable.
Vein visualizers have recently included augmented reality (AR) and virtual reality (VR) technologies. These developments enable a 3D visualisation of the veins by superimposing the vein image onto the patient's skin. the clarity and precision of vein visualisation have been significantly boosted by AR and VR technology.
Vein visualizers are still being developed, including software improvements, image technology and device miniaturisation. these changes are intended to increase healthcare practitioners’ access to vein visualization and to make it more affordable and convenient.
It's crucial to remember that, despite the impressive advancements made in the history of vein visualizer development, these tools cannot replace the knowledge and abilities of healthcare professionals. venipuncture operations must still be carried out safely and accurately, which calls for appropriate training and knowledge.
1.US10889860B2:- “Vein Visualization Device and Method”: This patent describes a vein visualization device that uses NIR(Near Infrared Rays) to display veins on the surface of the skin.
2.US9763613B2:-“Vein Imaging System and Method”: This patent describes a device that uses a method for imaging veins using infrared light and image processing techniques.
3.US10361259B2:- “Handheld Vein Visualization Device”:This patent describes a device that is portable and handheld device, which is used to identify veins and display veins on the surface of the skin.
4.US9897520B2:-“Vein Imaging System with Adjustable Light Intensity”:This patent describes a device that is used to locate veins by adjusting the light intensity for optimal vein visualization.
5.US9993072B2:- “Method and System for Vein Pattern Detection”: This patent describes a device that uses image analysis techniques and infrared rays for visualizing veins.
Summary of the Invention
A vein visualiser is used for visualising the veins, which makes it easier for healthcare professionals by reducing the stress involving finding veins and making it easier for patients by reducing pain and discomfort. This device uses infrared rays which gives a clear vision of veins when reflected on a body. Vein visualiser in the medical field can be used vastly in any sector of healthcare and it makes an everyday job simple and less time consuming
Brief Description of Drawings
The invention will be described in detail with reference to the exemplary embodiments shown in the figure wherein:
Figure 1: Diagrammatic representation of vein visualization
Detailed Description of the Invention
To improve the visualization of veins, a vein visualizer's operational method comprises the cooperation of hardware and software components.
Hardware Components,
1. Light Source: The vein visualizer uses a light source to illuminate the area where veins are to be seen. This light source is commonly near-infrared (NIR) or infrared light (IR) light. The source's light reacts with the blood in the veins to make them more noticeable.
2. Camera: A Camera records real-time photos or video of the lighted area. Usually, the camera has specialized sensors that can pick up the NIR or IR light that the veins reflect.
3. Image Processing Unit: An image processing unit processes the recorded pictures or videos and applies algorithms to improve the vein’s visibility. The veins are identified by analysis of the input data, which increases their contrast and makes them more noticeable against the background tissues.
4. Display Unit: The video or visuals that have been altered are then shown on a screen or directly projected onto the patient's skin. This enables medical personnel to see veins in real-time and precisely pinpoint the target vessels.
Software Components,
One popular algorithm used to build vein visualization systems is called the line projection technique. The line projection algorithm is widely employed for vein extraction and visualization in NIR imaging. Here's a high-level overview of the line projection technique:
Image Preprocessing: The input NIR image is preprocessed to enhance vein visibility and reduce noise. This step may include noise filtering, contrast enhancement, and image normalization.
Vein Enhancement: To enhance the vein structures, various image enhancement techniques can be applied. One common method is the application of an adaptive histogram equalization algorithm, which redistributes the pixel intensities to improve the visibility of veins.
Line Projection: The line projection algorithm is the core of the vein visualization process. It involves projecting lines onto the preprocessed image and analyzing the responses to detect veins.
a. Line Generation: Lines are generated at different orientations and lengths across the image.
b. Line Integration: Each line is integrated by summing the pixel intensities along its path.
c. Vein Response Calculation: The vein response is calculated by analyzing the integrated line profile. Veins exhibit higher responses due to their distinctive characteristics.
Vein Segmentation: Based on the calculated vein responses, a thresholding or adaptive thresholding technique is applied to segment the veins from the background tissue. The thresholding process separates the pixels with high responses (likely belonging to veins) from the rest.
Post-processing: The segmented vein regions may undergo additional post-processing to refine the visualization and remove any artifacts or noise. Morphological operations, such as erosion or dilation, may be used to improve vein connectivity or remove small irrelevant regions.
Visualization and Display: Finally, the segmented veins are visualized and displayed to the user. The veins may be overlaid on the original image or presented as a separate visualization, depending on the specific application. It's worth noting that there are variations and advancements to the line projection algorithm, such as incorporating machine learning techniques or incorporating 3D imaging for more accurate vein visualization. The specific implementation details and optimizations can vary depending on the system requirements and imaging technology used.

Connection:
The vein visualizer's hardware and software parts are tightly integrated. The image processing unit uses software algorithms to process the photos or videos that the camera has captured. The processed photos are shown in real time on the screen or projected onto the patient's skin giving the medical professional quick visual feedback.
Working:
1. Illumination: To illuminate the area where veins need to be seen, the vein visualizer emits a certain wavelength of light, usually near-infrared light (NIR) or infrared (IR) light. The blood's haemoglobin partially absorbs the light once it passes through the skin.
2. Light Reflection: The veins stand out from the surrounding tissues because they reflect less light than the surrounding areas as a result of the absorbed light energy. The veins and the rest of the skin are contrasted as a result.
3. Imaging: The reflected light from the lit region is recorded by a camera or optical sensors. The camera may employ particular sensors or filters that are tuned to the NIR or IR light spectrum. The veins might be seen in the recorded pictures or videos.image processing techniques play a crucial role in vein visualization to enhance the visibility of veins and separate them from the surrounding tissue.
4. Image Processing:
Image processing technique plays a crucial role in vein visualization to enhance the visibility of veins.
Filtering: The filtering technique is applied to remove noise and enhance vein structures.
Contrast Enhancement: Contrast stretching methods can be employed to enhance vein visibility by redistributing the pixel intensities across the image.
Thresholding: Thresholding techniques are used to separate veins from the background by selecting an appropriate intensity threshold. Simple thresholding sets a fixed threshold value, while adaptive thresholding adjusts the threshold locally to account for intensity variations within the image.
Edge Detection: Edge detection algorithms identify the boundaries and edges of veins, which are useful for vein segmentation.
Morphological Operations: Morphological operations, such as dilation and erosion, are used to refine and enhance the vein structures. These operations help bridge gaps between veins, fill small gaps or holes, and improve vein connectivity.
Region Growing: Region growing algorithms can be employed to segment veins based on the connectivity and similarity of neighboring pixels. The algorithm starts with a seed point and iteratively adds neighboring pixels that meet specific criteria, such as intensity similarity or gradient continuity.
Image Normalization: Image normalization techniques are used to adjust the image intensity values to a standardized range, improving the consistency and comparability of vein visualization across different images and lighting conditions.
Multi-scale Analysis: Multi-scale analysis techniques, such as multi-resolution analysis or wavelet transforms, can be utilized to capture veins at different scales. These methods analyze the image at multiple resolutions or using different filters to extract veins of varying widths and depths.
Additional capabilities of the vein visualizer could include the ability to switch between veins of various sizes, multiple imaging modes, and adjustable light intensity. Based on the particular patient and treatment requirements, these aspects can aid in optimizing vein visualization.
It is vital to remember that different versions and manufacturers may have slightly different operating mechanisms and vein visualizer components. To improve vein visualization and support precise vein targeting, some vein visualizers may also use other technologies, such as augmented reality (AR) or virtual reality (VR).
Advantages of the proposed model,
• The cost of the vein visualizer will be reduced and it will be more available in the market.
• Time consumption in finding veins will be reduced.
• The safety of the patient increases.
• Procedures involving veins will become very easy.
• In case of emergencies, the quick and accurate finding of the veins is crucial. It can be achieved by using a vein visualiser.
4 Claims & 1 Figure , Claims:The scope of the invention is defined by the following claims:
Claims:
1. The proposed invention vein visualization comprising,
a) A high-intensity laser is used instead of NIR that equally or almost penetrates the skin. The filtering technique is applied to remove noise and enhance vein structures.
b) A contrast stretching methods is employed to enhance vein visibility by redistributing the pixel intensities across the image.
c) A Thresholding techniques are used to separate veins from the background by selecting an appropriate intensity threshold.
2. A per claim 1, the edge detection algorithms identifies the boundaries and edges of veins, which are useful for vein segmentation. The Morphological operations, such as dilation and erosion, are used to refine and enhance the vein structures.
3. A per claim 1, the region growing algorithms is employed to segment veins based on the connectivity and similarity of neighboring pixels. The image normalization techniques are used to adjust the image intensity values to a standardized range, improving the consistency and comparability of vein visualization across different images and lighting conditions.
4. As per claim 1, the multi-scale analysis techniques are utilized to capture veins at different scales. These methods analyze the image at multiple resolutions or using different filters to extract veins of varying widths and depths.