AI PRODUCTS ❯
Lunit
DIB-MG

Parent Company:

Lunit

Product:

DIB-MG

DIB-MG learns radiologic features from large scale images without any human annotations. 

For the algorithm development, a total of 29,107 digital mammograms from five institutions (4,339 cancer cases and 24,768 normal cases) were included in the data sets. 

The core algorithm of DIB-MG is a deep convolutional neural network – a deep learning algorithm specialised for images. Each sample (case) is an exam composed of 4-view images (RCC, RMLO, LCC, and LMLO). For each case in a training set, the cancer probability inferred from DIB-MG is compared with the per-case ground-truth label. Then the model parameters in DIB-MG are updated based on the error between the prediction and the ground-truth.

anatomy
Breast
Subspecialty
Breast
Modality
Any
Pending
Research
Lunit Chest
Anatomy:
Chest
subspeciality:
Chest
Modality:
XR
Pending
N/A - Unknown
details