LAMISDMDB / LAMISDMDB_Sample

Our new mammography database, LAMISDMDB, can give a breakthrough in detecting and classifying breast cancer. It is ready to use ML and DL algorithms to detect and classify different cancers within the breasts accurately. This database has a large size as compared to other public mammogram databases.

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

LAMISDMDB

Mammography databases are an invaluable tool for medical professionals and researchers in diagnosing, monitoring and treating breast cancer. These databases aim to provide clinicians with comprehensive datasets that can be used for better decision-making when diagnosing patients with early signs or symptoms associated with breast cancer.

Our new mammography database, LAMISDMDB, can give a breakthrough in detecting and classifying breast cancer. It is ready to use ML and DL algorithms to detect and classify different cancers within the breasts accurately. This database has a large size as compared to other public mammogram databases; this allows for more detailed analysis when it comes to detecting abnormalities or malignant tumors. Additionally, users can download images based on any combination of structures such as BIRADS (Breast Imaging Reporting And Data System), ACR (American College Of Radiology), normal/benign/malignant classifications, etc., allowing for even more accuracy when analyzing potential cases. In conclusion, LAMISDMDB aims to revolutionize how we diagnose breast cancer by providing accurate information. This makes it easier for medical professionals worldwide to ensure their patients get the best care possible no matter where they live, helping save countless lives yearly which would otherwise succumb to diseases like these due to lack of proper diagnosis time. To get more details about the database, contact us through email: mohamed.amroune@univ-tebessa.dz.

About

Our new mammography database, LAMISDMDB, can give a breakthrough in detecting and classifying breast cancer. It is ready to use ML and DL algorithms to detect and classify different cancers within the breasts accurately. This database has a large size as compared to other public mammogram databases.