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6 papers · 1 filter
Distilling Missing Modality Knowledge from Ultrasound for Endometriosis Diagnosis with Magnetic Resonance Images
Yuan Zhang, Hu Wang, David Butler +4
Endometriosis is a common chronic gynecological disorder that has many characteristics, including the pouch of Douglas (POD) obliteration, which can be diagnosed using Transvaginal…
Mutual information neural estimation for unsupervised multi-modal registration of brain images
Gerard Snaauw, Michele Sasdelli, Gabriel Maicas +4
Many applications in image-guided surgery and therapy require fast and reliable non-linear, multi-modal image registration. Recently proposed unsupervised deep learning-based regis…
A Hierarchical Multi-Task Approach to Gastrointestinal Image Analysis
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
A large number of different lesions and pathologies can affect the human digestive system, resulting in life-threatening situations. Early detection plays a relevant role in the su…
Double Encoder-Decoder Networks for Gastrointestinal Polyp Segmentation
Adrian Galdran, Gustavo Carneiro, Miguel A. González Ballester
Polyps represent an early sign of the development of Colorectal Cancer. The standard procedure for their detection consists of colonoscopic examination of the gastrointestinal trac…
Brain tumour segmentation using a triplanar ensemble of U-Nets
Vaanathi Sundaresan, Ludovica Griffanti, Mark Jenkinson
Gliomas appear with wide variation in their characteristics both in terms of their appearance and location on brain MR images, which makes robust tumour segmentation highly challen…
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
Ali H. Al-Timemy, Rami N. Khushaba, Zahraa M. Mosa +1
Clinicians in the frontline need to assess quickly whether a patient with symptoms indeed has COVID-19 or not. The difficulty of this task is exacerbated in low resource settings t…