Diagnosis Breast cancer Mammogram − Detection, Calcification, BIRADS, Segmentation
1

Tumor Detection

Radiologists can submit mammography image to Cancer Moonshot AI software running on the cloud. Cancer Moonshot AI software interprets the mammogram to detect the tumor location and presents the result instantly.

Benign/Malignant

Radiologists can submit tumor patches image to Cancer Moonshot AI software running on the cloud. Cancer Moonshot AI software interprets the mammogram tumor patches and presents the result instantly in terms of benign and malignancy prediction.
2
3

Calcification

Radiologists will be able to identify typically benign/malignant breast calcifications that do not require biopsy to prevent unnecessary procedures and to reduce patient anxiety.

BIRADS Classification

Radiologists can categorize mammogram for breast cancer diagnosis into a small number of well-defined categories. BIRADS mainly benefits the Radiologists who report mammogram findings.
4
5

Tumor Segmentation and quantification

Radiologists will be able to segment the tumor and can quantify the tumor dimensions for deep diagnosis of cancer
Therapeutic response and recurrence for Breast cancer − MRI Modalities Neoadjuvant chemotherapy with Anthracycline and Taxane

MRI Response

Physicians can submit MRI series images to predict the treatment response for the prognosis. Cancer Moonshot AI can interpret the images and it can predict , whether a patient can respond for a particular drug. Helps in designing personalized treatments, avoids treatment failure thus saves time money and efforts for both patents and physicians.