831 citations · 1.4k across the 28 of their papers we have counts for
30 papers
MIRTO: a registration-gated, multiverse-tested evaluation protocol for unsupervised anomaly segmentation in brain MRI
Negin Kafee Hernashki, Soumick Chatterjee
Unsupervised anomaly detection (UAD) methods for brain MRI are ranked by a single score, yet that score rests on choices that are rarely reported: how each anomaly map is aligned w…
Towards Segmenting the Invisible: An End-to-End Registration and Segmentation Framework for Weakly Supervised Tumour Analysis
Budhaditya Mukhopadhyay, Chirag Mandal, Pavan Tummala +3
Liver tumour ablation presents a significant clinical challenge: whilst tumours are clearly visible on pre-operative MRI, they are often effectively invisible on intra-operative CT…
SPOCKMIP: Segmentation of Vessels in MRAs with Enhanced Continuity using Maximum Intensity Projection as Loss
Chethan Radhakrishna, Karthikesh Varma Chintalapati, Sri Chandana Hudukula Ram Kumar +5
Identification of vessel structures of different sizes in biomedical images is crucial in the diagnosis of many neurodegenerative diseases. However, the sparsity of good-quality an…
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation
Soumick Chatterjee, Franziska Gaidzik, Alessandro Sciarra +5
In the domain of medical imaging, many supervised learning based methods for segmentation face several challenges such as high variability in annotations from multiple experts, pau…
Complex-valued neural networks to speed-up MR Thermometry during Hyperthermia using Fourier PD and PDUNet
Rupali Khatun, Soumick Chatterjee, Christoph Bert +6
Hyperthermia (HT) in combination with radio- and/or chemotherapy has become an accepted cancer treatment for distinct solid tumour entities. In HT, tumour tissue is exogenously hea…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…