most citedW-Net: Dense Semantic Segmentation of Subcutaneous Tissue in Ultrasound Images by Expanding U-Net to Incorporate Ultrasound RF Waveform Data

1 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2022★ 1 cited

AI-augmented histopathologic review using image analysis to optimize DNA yield and tumor purity from FFPE slides

Bolesław L. Osinski, Aïcha BenTaieb, Irvin Ho +8

To achieve minimum DNA input and tumor purity requirements for next-generation sequencing (NGS), pathologists visually estimate macrodissection and slide count decisions. Misestima…

eess.IV2020★ 1 cited

W-Net: Dense Semantic Segmentation of Subcutaneous Tissue in Ultrasound Images by Expanding U-Net to Incorporate Ultrasound RF Waveform Data

Gautam Rajendrakumar Gare, Jiayuan Li, Rohan Joshi +5

We present W-Net, a novel Convolution Neural Network (CNN) framework that employs raw ultrasound waveforms from each A-scan, typically referred to as ultrasound Radio Frequency (RF…