Electronic Resource
Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours
| العنوان: | Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours |
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| المؤلفون: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group, Hernández Pérez, Carlos, Combalia Escudero, Marc, Puig Sardá, Susana, Malvehy Guilera, Josep, Vilaplana Besler, Verónica |
| بيانات النشر: | Springer 2022-09-30 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Sentinel lymph node status is a crucial prognosis factor for melanomas; nonetheless, the invasive surgery required to obtain it always puts the patient at risk. In this study, we develop a Deep Learning-based approach to predict lymph node metastasis from Whole Slide Images of primary tumours. Albeit very informative, these images come with complexities that hamper their use in machine learning applications, namely their large size and limited datasets. We propose a pre-training strategy based on self-supervised contrastive learning to extract better image feature representations and an attention-based Multiple Instance Learning approach to enhance the model’s performance. With this work, we quantitatively demonstrate that combining both methods improves various classification metrics and qualitatively show that contrastive learning encourages the network to output higher attention scores to tumour tissue and lower scores to image artifacts. Work supported by the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/AEI/10.13039/501100011033 and the project 718/C/ 2019 funded by Fundació la Marato de TV3. Peer Reviewed Postprint (author's final draft) |
| مصطلحات الفهرس: | Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo, Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic, Deep learning, Melanoma, Artificial intelligence -- Medical applications, Whole slide image, Contrastive learning, Attention-based multiple instance learning, Early detection, Aprenentatge profund, Intel·ligència artificial -- Aplicacions a la medicina, Part of book or chapter of book |
| URL: | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116907RB-I00/ES/INTELIGENCIA ARTIFICIAL INSESGADA Y EXPLICABLE PARA IMAGENES MEDICAS |
| الاتاحة: | Open access content. Open access content Open Access |
| ملاحظة: | 10 p. application/pdf English |
| Other Numbers: | HGF oai:upcommons.upc.edu:2117/384779 Hernández, C. [et al.]. Contrastive and attention-based multiple instance learning for the prediction of sentinel lymph node status from histopathologies of primary melanoma tumours. A: "Cancer Prevention Through Early Detection: First International Workshop, CaPTion 2022: Held in Conjunction with MICCAI 2022: Singapore, September 22, 2022: proceedings". Berlín: Springer, 2022, p. 57-66. 978-3-031-17979-2 10.1007/978-3-031-17979-2_6 1379093662 |
| المصدر المساهم: | UNIV POLITECNICA DE CATALUNYA From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1379093662 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |