EIRL | NEXT MEDICAL VISION | LPixel Inc.

Another set of powerful eyes to
support future medical diagnosis.

EIRL is the next medical image diagnostic support technology
to catalyze the coming generation of medical diagnosis.

EIRL's Story

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Vision

Another set of powerful eyes to
support future medical diagnosis.
EIRL is the next medical image diagnostic support technology to catalyze the coming generation of medical diagnosis. Together with the constant advancements in modalities, comes the challenges for doctors to interpret an exponentially large number of images for diagnosis. EIRL aims to provide an accurate, accelerated and streamlined solution for medical diagnosis by analyzing a variety of information required for diagnosis. EIRL will be the closest partner to all doctors, and serve as another powerful set of eyes to provide top quality medical care. To all doctors around the world, EIRL.

Features

Expert-appoved Training Data
1. Expert-appoved Training Data

EIRL is powered by knowledge derived from experienced doctors. All the data used to train EIRL is double and triple checked by experienced doctors. The selection process is further refined as only the images that led to an accurate diagnosis are used to train EIRL.

Learning from Limited Data
2. Learning from Limited Data

EIRL is instilled with LPixel's unique active learning technology, namely CARTA, and other powerful tools to enable EIRL to generate training data with great precision and efficiency, even if the number training data available on hand is limited.

Accommodation to Images of Varying Quality
3. Accommodation to Images of Varying Quality

In clinical practice, images for diagnostic purposes are taken with an array of different image acquisition tools and protocols. EIRL is trained with a variety of training data acquired from a wide range of modalities and protocols, allowing for the robust output of highly accurate results.

Effortless Integration with PACS
4. Effortless Integration with PACS

EIRL can be integrated with the PACS that is currently being used in your institution.

Themes

  • Aneurysms

  • Stenosis

  • DESH

    disproportionately enlarged subarachnoid-space hydrocephalus

  • White Matter Lesions

  • Breast MRI Analysis

  • Chest X-Ray Triage

  • Classification of Lung Cancer CT Scans

  • Liver Cancer Image Analysis

  • Colonoscopy Image Analysis

  • 3D Construction of Pathology Images

  • Aneurysms
    Aneurysms
    Our technology works on MRA scans to detect patterns that are similar to vascular deformations and unruptured cerebral aneurysms. The thorough analysis helps to keep the number of overlooked aneurysms to a minimum.
  • Stenosis
    Stenosis
    In efforts to reduce the number of misdiagnosed cases of cerebral arterial stenosis, our technology conducts a careful analysis of MRA scans to detect patterns that are similar to cerebral arterial stenosis.
  • DESH
    DESH
    disproportionately enlarged subarachnoid-space hydrocephalus
    Our technology automatically calculates the Evans index and the callosal angle, both of which serve as helpful biomarkers for the diagnosis of Disproportionately Enlarged Subarachnoid Space Hydrocephalus (DESH) among patients diagnosed with idiopathic normal
    pressure hydrocephalus (iNPH).
  • White Matter Lesions
    White Matter Lesions
    This analyzes MRI scans to detect areas that are suspected to contain white matter lesions. Our aims moving forward will be to classify the diagnostic certainty of each of the cases from quantitative data, such as the volume ratio of white matter lesions to normal regions.
  • Breast MRI Analysis
    Breast MRI Analysis
    This technology conducts a time-intensity curve (TIC) analysis for MRI scans of the breasts. We hope to identify the degree of malignancy of the tumor by using machine learning technology, the results of the TIC shape analysis and other information extracted from the images.
  • Chest X-Ray Triage
    Chest X-Ray Triage
    This computer-aided CXR triage categorizes X-ray images. By automatically identifying and highlighting suspicious regions in the lungs, doctors can screen patients who require further attention and offer treatment options faster. This streamlined solution gives patients opportunities for early treatment and improved healthcare services at the same, or reduced costs.
  • Classification of Lung Cancer CT Scans
    Classification of Lung Cancer CT Scans
    This is powered by LPixel’s patented active learning technology, “CARTA.” Currently under development with the National Cancer Center in Japan, this cutting edge technology targets lung cancer CT scans to automatically identify the type of lung cancer and gene mutation, opening doors to imaging-based treatment options for patients. By reducing the need for highly invasive biopsies, this technology is anticipated to significantly improve the patient’s quality of life.

    *The image is for illustration purposes.
  • Liver Cancer Image Analysis
    Liver Cancer Image Analysis
    Contrast agents serve as a powerful tool in the diagnosis process for liver cancer as they greatly enhance the visibility of the tumors. Once the contrast agents have been administered, the MRI scans of the liver are then further analyzed and monitored over a period of time to look for regions that may contain tumors.
  • Colonoscopy Image Analysis
    Colonoscopy Image Analysis
    This interoperates video images during colonoscopic examination in real-time. It can display the areas in the colon where the risk of lesions, such as tumors, are high, which will help to decrease the number of overlooked lesions. This technology is being developed in collaboration with the Jikei University School of Medicine in Tokyo.

    *The images used in the demo video was provided by the Jikei University.
  • 3D Construction of Pathology Images
    3D Construction of Pathology Images
    Three-dimensional construction of pathological images is performed by interpolation processing and positioning. This makes it possible to view the three-dimensional structure of the cell and its mutations. This three-dimensional information serves as a powerful aid in diagnosing patients with kidney disease, among others.This project is led by the Ministry of Economy, Trade and Industry in Japan as part of the Strategic Core Technology Advancement Program. LPixel is working in collaboration with TCK Co., Ltd. and others.

    *The pathological samples used in the demo video was provided by Kurume University.

Awards

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Story about EIRL

  • LPixel

EIRL was born between LPixel and Eir*, the Norse goddess associated with healing and medical skill. The logo illustrates the unison of doctors and EIRL, and the circle in the center represents the overlapping eyes of doctors and EIRL seeking for the one and only truth. EIRL will be a vital presence in the medical field, working alongside and supporting doctors in future medical diagnosis.