Search Results for author: Samuel Budd

Found 8 papers, 0 papers with code

Whole-examination AI estimation of fetal biometrics from 20-week ultrasound scans

no code implementations2 Jan 2024 Lorenzo Venturini, Samuel Budd, Alfonso Farruggia, Robert Wright, Jacqueline Matthew, Thomas G. Day, Bernhard Kainz, Reza Razavi, Jo V. Hajnal

We use a Bayesian method to estimate the true value of each biometric from a large number of measurements and probabilistically reject outliers.

Anatomy

Can non-specialists provide high quality gold standard labels in challenging modalities?

no code implementations30 Jul 2021 Samuel Budd, Thomas Day, John Simpson, Karen Lloyd, Jacqueline Matthew, Emily Skelton, Reza Razavi, Bernhard Kainz

We study the time and cost implications of using novice annotators, the raw performance of novice annotators compared to gold-standard expert annotators, and the downstream effects on a trained Deep Learning segmentation model's performance for detecting a specific congenital heart disease (hypoplastic left heart syndrome) in fetal ultrasound imaging.

Surface Agnostic Metrics for Cortical Volume Segmentation and Regression

no code implementations4 Oct 2020 Samuel Budd, Prachi Patkee, Ana Baburamani, Mary Rutherford, Emma C. Robinson, Bernhard Kainz

The cerebral cortex performs higher-order brain functions and is thus implicated in a range of cognitive disorders.

regression

3D Probabilistic Segmentation and Volumetry from 2D projection images

no code implementations23 Jun 2020 Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz

X-Ray imaging is quick, cheap and useful for front-line care assessment and intra-operative real-time imaging (e. g., C-Arm Fluoroscopy).

A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis

no code implementations7 Oct 2019 Samuel Budd, Emma C. Robinson, Bernhard Kainz

Fully automatic deep learning has become the state-of-the-art technique for many tasks including image acquisition, analysis and interpretation, and for the extraction of clinically useful information for computer-aided detection, diagnosis, treatment planning, intervention and therapy.

Active Learning

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