SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints

Autor: Basaran, Berke Doga, Zhang, Xinru, Matthews, Paul M., Bai, Wenjia

Assessment of lesions and their longitudinal progression from brain magnetic resonance (MR) images plays a crucial role in diagnosing and monitoring multiple sclerosis (MS). Machine learning models have demonstrated a great potential for automated MS

Externí odkaz: http://arxiv.org/abs/2410.01766

LesionMix: A Lesion-Level Data Augmentation Method for Medical Image Segmentation

Autor: Basaran, Berke Doga, Zhang, Weitong, Qiao, Mengyun, Kainz, Bernhard, Matthews, Paul M., Bai, Wenjia

Data augmentation has become a de facto component of deep learning-based medical image segmentation methods. Most data augmentation techniques used in medical imaging focus on spatial and intensity transformations to improve the diversity of training

Externí odkaz: http://arxiv.org/abs/2308.09026

Subject-Specific Lesion Generation and Pseudo-Healthy Synthesis for Multiple Sclerosis Brain Images

Autor: Basaran, Berke Doga, Qiao, Mengyun, Matthews, Paul M., Bai, Wenjia

Understanding the intensity characteristics of brain lesions is key for defining image-based biomarkers in neurological studies and for predicting disease burden and outcome. In this work, we present a novel foreground-based generative method for mod

Externí odkaz: http://arxiv.org/abs/2208.02135

Early versus delayed weight-bearing following operatively treated ankle fracture (WAX): a non-inferiority, multicentre, randomised controlled trial

Autor: McAndrew, Andrew, Jacobs, Neal, Forder, Justin, Hester, Thomas, Cross, Charlotte, Bateman, Tony, Kieffer, Will, Barton, Tristan, Walter, Richard, Savva, Nick, Marsland, Daniel, Rose, Barry, Beech, Zine, Koc, Togay, Armstead, Bethany, Ollivere, Ben, Diamond, Owen, Teoh, Kar, Magill, Paul, Mangwani, Jitendra, Hodgson, Paul, Ray, Robbie, Dhinsa, Baljinder, Majeed, Haroon, Wong-Chung, John, Young, Jonathan, Lagare, Agnes, Soogumbur, Akash, Morozova, Albina, Hunt, Alexander, Adamson, Amanda, Dempster, Angie, McCormack, Ann, Arif, Azra, Vye, Charlotte, Dojode, Chetan, Brown, Chloe, Haines, Christina, To, Christopher, Brennan, Ciaran, Winson, Dan, McGough, Elizabeth, Jessup-Dunton, Ellen, Bintcliffe, Fiona, Thompson, Fiona, Omogra, Gabriel, Scott, Georgia, Samuel, Helen, Fraig, Hossam, Burokiene, Ina, Odysseos-Beaumont, Isabel, Rand, James, Edkins, Janet, Barrett-Lee, Joe, McFall, John, Wahed, Karim, Herbert, Kate, Death, Kelly, Beddard, Laura, Dupley, Leanne, Bryce, Leeann, Wright, Lianne, Bailey, Lucy, Maling, Lucy, Raad, Marjan, Morris, Matt, Williams, Matthew, Labidi, May, Holmes, Natalie, Staines, Nikki, Matthews, Paul A, McCormac, Philip, Easow, Rashmi, Matthews, Scott, Kapoor, Smriti, Harris, Sophie, Wagland, Susan, Cobb, Timothy, White, Tracey, Bretherton, Christopher Patrick ^*, Achten, Juul, Jogarah, Vidoushee, Petrou, Stavros, Peckham, Nicholas, Achana, Felix, Appelbe, Duncan, Kearney, Rebecca, Claireux, Harry, Bell, Philip, Griffin, Xavier L

Publikováno v: In The Lancet 29 June-5 July 2024 403(10446):2787-2797

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