Latest News | Satsuma

Exploring Fairness and Performance Drivers Across State-of-the-Art Pulmonary Nodule Detection Algorithms

Mon, 04 May 2026 00:00:00 +0000

Researchers from Satsuma Lab have evaluated the fairness of deep learning based computer aided detection (CADe) systems for lung nodule detection in screening CT scans. Using data from a SUMMIT (London-based cohort), the study found that model performance remains consistent across sex and ethnic groups, despite imbalances in the training data. Results suggest that detection accuracy is driven more by nodule characteristics than by demographic factors. These findings support the equitable deployment of AI tools in future UK lung cancer screening programmes.

Further details can be found in John McCabe et al., 2025.

A hybrid CNN-RNN approach for survival analysis in a Lung Cancer Screening study

Fri, 29 Sep 2023 00:00:00 +0000

Researchers from Satsuma Lab have introduced a hybrid approach combining Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) to predict long-term survival in a Lung Cancer Screening (LCS) study. It was demonstrated that incorporating the patient’s imaging follow-up history can lead to improvement in survival prediction. Delineating subjects at increased risk of cardiorespiratory mortality can alert clinicians to request further more detailed functional or imaging studies to improve the assessment of cardiorespiratory disease burden. Such strategies may uncover unsuspected and under-recognised pathologies thereby potentially reducing patient morbidity.

Further details can be found in Lu et al., 2023.

Moucheng Named Finalist for MICCAI Young Scientist Award (Best Paper Award)

Wed, 10 May 2023 00:00:00 +0000

Satsuma Lab is delighted to announce that Moucheng was named a finalist for the MICCAI Young Scientist Award for his paper: Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation (Semi-Supervised Segmentation with Pseudo Labels). A journal extension can be found here: Expectation Maximization Pseudo Labelling for Segmentation with Limited Annotations

The MICCAI Young Scientist Award recognizes the best papers that are first-authored by young scientists at the main MICCAI conference. This award is regarded as one of the most prestigious and most competitive award in the field of medical image computing. Each year has 5 winners, 15 finalists and 30 nominations. In 2022, there were 1825 total submissions, making Moucheng’s paper top 0.8 % among all of the submissions.

Satsuma Lab @ CMIC Away Day 2022

Fri, 20 May 2022 00:00:00 +0000

Satsuma Lab had a great time at the Centre for Medical Imaging (CMIC) away day!

Spending two days engaging with fellow medical image Core and labs in the centre. Thank you to all for a great event.

Satsuma Lab @ BMVA 2022 Symposium

Mon, 04 Apr 2022 00:00:00 +0000

Satsuma Lab presenting two posters at the special BMVA symposium 2022 in Manchester, UK!

Checkout our posters on:

Outreach video - Imaging for Cystic Fibrosis

Fri, 11 Mar 2022 00:00:00 +0000

Cystic Fibrosis is one of the key diseases that we’re working towards understanding with CT imaging here in the Satsuma Lab. Check out this video

explaining the motivation behind imaging research for Cystic Fibrosis.

Our group website is now live!

Tue, 19 Oct 2021 00:00:00 +0000

After 3 active years, the Satsuma research group based within the Centre for Medical Image Computing at University College London has its very own website.

We will publish and share our latests updates right here for all to see. From academic paper publications to public engagement videos this will be the place to find out what we’re up to!