no code implementations • 27 May 2024 • Syed Javed, Tariq M. Khan, Abdul Qayyum, Arcot Sowmya, Imran Razzak
Accurate segmentation of anatomical structures and abnormalities in medical images is crucial for computer-aided diagnosis and analysis.
no code implementations • 19 Feb 2024 • Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya, Erik Meijering
Survival risk stratification is an important step in clinical decision making for breast cancer management.
no code implementations • 16 Feb 2024 • Raktim Kumar Mondol, Ewan K. A. Millar, Arcot Sowmya, Erik Meijering
A co-dual-cross-attention mechanism combines the histopathological features with genetic data, enabling the model to capture the interplay between them.
no code implementations • 17 Jan 2024 • Sonit Singh, Gordon Stevenson, Brendan Mein, Alec Welsh, Arcot Sowmya
Methods: We propose an automatic three-dimensional multi-modal (B-mode and power Doppler) ultrasound segmentation of the human placenta using deep learning combined with different fusion strategies. We collected data containing Bmode and power Doppler ultrasound scans for 400 studies.
no code implementations • 16 Oct 2023 • Shisheng Zhang, Ramtin Gharleghi, Sonit Singh, Arcot Sowmya, Susann Beier
Coronary artery diseases are among the leading causes of mortality worldwide.
no code implementations • 25 Sep 2023 • Md Akizur Rahman, Sonit Singh, Kuruparan Shanmugalingam, Sankaran Iyer, Alan Blair, Praveen Ravindran, Arcot Sowmya
Pyramid pooling (PyP) and channel-spatial Squeeze and Excitation (csSE) were also used to improve the model performance.
no code implementations • 20 Sep 2023 • Louisa Canepa, Sonit Singh, Arcot Sowmya
Medical visual question answering (Med-VQA) is a machine learning task that aims to create a system that can answer natural language questions based on given medical images.
1 code implementation • 30 Aug 2023 • Jianning Li, Zongwei Zhou, Jiancheng Yang, Antonio Pepe, Christina Gsaxner, Gijs Luijten, Chongyu Qu, Tiezheng Zhang, Xiaoxi Chen, Wenxuan Li, Marek Wodzinski, Paul Friedrich, Kangxian Xie, Yuan Jin, Narmada Ambigapathy, Enrico Nasca, Naida Solak, Gian Marco Melito, Viet Duc Vu, Afaque R. Memon, Christopher Schlachta, Sandrine de Ribaupierre, Rajnikant Patel, Roy Eagleson, Xiaojun Chen, Heinrich Mächler, Jan Stefan Kirschke, Ezequiel de la Rosa, Patrick Ferdinand Christ, Hongwei Bran Li, David G. Ellis, Michele R. Aizenberg, Sergios Gatidis, Thomas Küstner, Nadya Shusharina, Nicholas Heller, Vincent Andrearczyk, Adrien Depeursinge, Mathieu Hatt, Anjany Sekuboyina, Maximilian Löffler, Hans Liebl, Reuben Dorent, Tom Vercauteren, Jonathan Shapey, Aaron Kujawa, Stefan Cornelissen, Patrick Langenhuizen, Achraf Ben-Hamadou, Ahmed Rekik, Sergi Pujades, Edmond Boyer, Federico Bolelli, Costantino Grana, Luca Lumetti, Hamidreza Salehi, Jun Ma, Yao Zhang, Ramtin Gharleghi, Susann Beier, Arcot Sowmya, Eduardo A. Garza-Villarreal, Thania Balducci, Diego Angeles-Valdez, Roberto Souza, Leticia Rittner, Richard Frayne, Yuanfeng Ji, Vincenzo Ferrari, Soumick Chatterjee, Florian Dubost, Stefanie Schreiber, Hendrik Mattern, Oliver Speck, Daniel Haehn, Christoph John, Andreas Nürnberger, João Pedrosa, Carlos Ferreira, Guilherme Aresta, António Cunha, Aurélio Campilho, Yannick Suter, Jose Garcia, Alain Lalande, Vicky Vandenbossche, Aline Van Oevelen, Kate Duquesne, Hamza Mekhzoum, Jef Vandemeulebroucke, Emmanuel Audenaert, Claudia Krebs, Timo Van Leeuwen, Evie Vereecke, Hauke Heidemeyer, Rainer Röhrig, Frank Hölzle, Vahid Badeli, Kathrin Krieger, Matthias Gunzer, Jianxu Chen, Timo van Meegdenburg, Amin Dada, Miriam Balzer, Jana Fragemann, Frederic Jonske, Moritz Rempe, Stanislav Malorodov, Fin H. Bahnsen, Constantin Seibold, Alexander Jaus, Zdravko Marinov, Paul F. Jaeger, Rainer Stiefelhagen, Ana Sofia Santos, Mariana Lindo, André Ferreira, Victor Alves, Michael Kamp, Amr Abourayya, Felix Nensa, Fabian Hörst, Alexander Brehmer, Lukas Heine, Yannik Hanusrichter, Martin Weßling, Marcel Dudda, Lars E. Podleska, Matthias A. Fink, Julius Keyl, Konstantinos Tserpes, Moon-Sung Kim, Shireen Elhabian, Hans Lamecker, Dženan Zukić, Beatriz Paniagua, Christian Wachinger, Martin Urschler, Luc Duong, Jakob Wasserthal, Peter F. Hoyer, Oliver Basu, Thomas Maal, Max J. H. Witjes, Gregor Schiele, Ti-chiun Chang, Seyed-Ahmad Ahmadi, Ping Luo, Bjoern Menze, Mauricio Reyes, Thomas M. Deserno, Christos Davatzikos, Behrus Puladi, Pascal Fua, Alan L. Yuille, Jens Kleesiek, Jan Egger
For the medical domain, we present a large collection of anatomical shapes (e. g., bones, organs, vessels) and 3D models of surgical instrument, called MedShapeNet, created to facilitate the translation of data-driven vision algorithms to medical applications and to adapt SOTA vision algorithms to medical problems.
1 code implementation • 10 Apr 2023 • Raktim Kumar Mondol, Ewan K. A. Millar, Peter H Graham, Lois Browne, Arcot Sowmya, Erik Meijering
Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC).
1 code implementation • 3 Nov 2022 • Ramtin Gharleghi, Dona Adikari, Katy Ellenberger, Mark Webster, Chris Ellis, Arcot Sowmya, Sze-Yuan Ooi, Susann Beier
Cases were classified as normal (zero calcium score with no signs of stenosis) or diseased (confirmed coronary artery disease).
no code implementations • 11 Sep 2022 • Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev, Henry Brodaty, Arcot Sowmya
This method uses temporal abstraction to convert the data into a more appropriate form for modelling, temporal pattern mining, to discover patterns in the complex, longitudinal data and machine learning models of survival analysis to select the discovered patterns.
no code implementations • 6 Jul 2022 • Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev, Henry Brodaty, Arcot Sowmya
When feature selection is applied to these datasets to identify the most important features, the biases inherent in some multivariate feature selectors due to correlated features make it difficult for these methods to distinguish between the important and irrelevant features and the results of the feature selection process can be unstable.
no code implementations • 5 Jul 2022 • Annette Spooner, Gelareh Mohammadi, Perminder S. Sachdev, Henry Brodaty, Arcot Sowmya
A fixed threshold, which is typically applied, offers no guarantee that the final set of selected features contains only relevant features.
no code implementations • 4 Jul 2022 • Hongyan Xu, Dadong Wang, Arcot Sowmya
However, in CT and CXR images, the infected area occupies only a small part of the image.
no code implementations • 6 Dec 2021 • Sankaran Iyer, Alan Blair, Laughlin Dawes, Daniel Moses, Christopher White, Arcot Sowmya
The results of experiments on localisation of the Spleen, Left and Right Kidneys in CT Images using supervised and semi supervised learning (SSL) demonstrate the ability to address data limitations with a much smaller data set and fewer annotations, compared to other state-of-the-art methods.
no code implementations • 4 Nov 2020 • Nuha Aldausari, Arcot Sowmya, Nadine Marcus, Gelareh Mohammadi
Then, a comprehensive review of video GANs models is provided under two main divisions according to the presence or non-presence of a condition.
no code implementations • 16 Sep 2020 • Mina Ghaffari, Arcot Sowmya, Ruth Oliver
In this paper, we propose a deep-learning based method to segment a brain tumour into its subregions: whole tumour, tumour core and enhancing tumour.
no code implementations • 29 Oct 2019 • Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen
In this paper, we consider the sigmoid Gaussian Hawkes process model: the baseline intensity and triggering kernel of Hawkes process are both modeled as the sigmoid transformation of random trajectories drawn from Gaussian processes (GP).
no code implementations • 29 May 2019 • Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen
In classical Hawkes process, the baseline intensity and triggering kernel are assumed to be a constant and parametric function respectively, which limits the model flexibility.