UR Research
metadata only
Deep learning for medical imaging : automated ultrasound diagnosis and physics-informed elastography reconstructionn
Thesis (Ph. D.)--University of Rochester. Department of Electrical and Computer Engineering, 2026.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Deep Learning for Ultrasound Imaging: From Task-Specific Architectures to Foundation Models#651630
- Image quality improvement of liver ultrasound using unsupervised deep learning.#143135
- A deep learning framework for standardized interpretation of multiparameter cardiac ultrasound and disease classification.#436999
- Advancing Ultrasound Beamforming With Deep Learning: A Comprehensive Review of Methods, Datasets, Benchmarks, and Computational Challenges.#1189243
- A modular deep learning pipeline for standardised analysis of pelvic ultrasound images for gynaecology#231417
Record · ID 1368589
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive