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Semi-Automatic Solution for Medical Image Data

By semi-automating the labeling work, high accuracy can be achieved while reducing the data processing time by a tenth.

MediLabel

MediLabel is a deep learning-based medical image labeling software focused on user convenience. It has the characteristic of being able to label large-scale medical data at high speed by learning user labeling patterns.

MediLabel Demo Request

You can try a demo of MediLabel for 14days.
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Detail feature of MediLabel

Visualization

  • Supports Axial, Sagittal, Coronal views

  • Provides Label overlay function

  • Provides video Zoom/Pan function

  • Provides image windowing function

  • Provide a four split screen

  • Provides 3D rendering function

Image Segmentation

  • A Semi-Automatic Labeling of 2D( Smart pencil, Smart fill)

  • Semi-Automatic Labeling of 3D( 3D fill)

  • Fully automatic labeling and segmentation of normal structures (AI templates)

  • Threshold can be changed when using graph-based segmentation method

  • Provides the ability to export segmentation results to Label Data

Project Management

  • Manage various image format images as lists and groups

  • Upload files conveniently with drag & drop

  • Shortcut customization capabilities

  • Simultaneous upload of multiple folders (patient data management by folder)

  • Ability to label, verify, modify, and exchange feedbacks

  • Data analysis and statistics dashboard capabilities

  • Initial data learning and automation capabilities

  • PACS Interworking and Large Data Upload Capabilities

Support Data

  • Available in on-premise version (for internal installation)

  • Supported 2D image data : png, jpg/jpeg, bmp, tiff

  • Supported Medical Image Data : nii, DICOM(single frame support), ultrasonic waves

Clients & Partners

"This is your Testimonial section paragraph. It’s a great place to tell users how much you value your customers and their feedback, and read below to hear reviews straight from the source. Let your sparkling feedback speak for itself.

Parker Stuart

Client Review

This is your Testimonial section paragraph. It’s a great place to tell users how much you value your customers and their feedback, and read below to hear reviews straight from the source. Let your sparkling feedback speak for itself.

Payton Hillman

Client Review

This is your Testimonial section paragraph. It’s a great place to tell users how much you value your customers and their feedback, and read below to hear reviews straight from the source. Let your sparkling feedback speak for itself.

Riley Jones

Client Review

Testimonials

Smart Pencil

A feature to cluster pixels and accurately label multiple pixels with one click using deep learning AI algorithms. It is the ability to predict labeling outputs visually before clicking.

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Smart Fill

A feature that easily labels difficult areas such as cerebral infarction, tumors, and normal structure when you create the bounding box, it details the target in the box and automatically labels it.

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Auto Correction

A feature that leverages deep learning algorithms to smooth out boundary values or fill in empty spaces saves time and cost in the labeling modification process and improves quality.

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Project Management

A feature to easily manage a large data of patients. Improves work efficiency by naming each data as a folder and checking the progress of work.

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Email / info@ingradient.com

Telephone / +82 2 6959 0503

Address / 27, Teheran-ro 2-gil,  Yeoksam-dong, Gangnam-gu, Seoul, KR

© 2021 Ingradient, Inc.

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