We have proposed a fully convolutional approach for high-density compression of mammograms without loss of. 32593. Page 4. (a) Tested on CBIS-DDSM. (b) Tested ...

May 17, 2018 · We demonstrate performance on two different publicly available digital mammography datasets using peak signal-to-noise ratio (pSNR), structural ...

This work proposes a fully convolutional autoencoder for diagnostically relevant feature preserving lossy compression and demonstrates performance on two ...

We demonstrate performance on two different publicly available digital mammography datasets using peak signal-to-noise ratio (pSNR), structural similarity (SSIM) ...

Bibliographic details on Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms.

Article "Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms" Detailed information of the J-GLOBAL is an ...

Apr 12, 2021 · This study aims to classify a mammogram as either normal/benign or malignant using a DL-based model.

Explore all code implementations available for Fully Convolutional Model for Variable Bit Length and Lossy High Density Compression of Mammograms.

Fully convolutional model for variable bit length and lossy high density compression of mammograms. A Kar, S Phani Krishna Karri, N Ghosh, R Sethuraman, D Sheet.

May 17, 2018 · Fully Convolutional Model for Variable Bit Length and Lossy High Density. Compression of Mammograms. Aupendu Kar, Sri Phani Krishna Karri ...