Results 71 to 80 of about 170,175 (308)

Mixed-block neural architecture search for medical image segmentation [PDF]

, 2022
Deep Neural Networks (DNNs) have the potential for making various clinical procedures more time-efficient by automating medical image segmentation. Due to their strong, in some cases human-level, performance, they have become the standard approach in ...
Dushatskiy, A. (author), Grewal, M. (author), Bosma, M.M.A. (Martijn), Dushatskiy, A. (Arkadiy), Bosman, P.A.N. (author), Bosman, P.A.N. (Peter), Alderliesten, T. (Tanja), Grewal, M. (Monika), Bosma, Martijn M.A. (author), Alderliesten, T. (author)   +9 more
core   +1 more source

Correction Learning for Medical Image Segmentation [PDF]

IEEE Access, 2019
Breast tumor segmentation is useful to diagnose breast cancer. However, challenges, such as intensity inhomogeneity and shadowing artifacts arise in this task. To address these two issues, this paper proposes a robust ultrasound image segmentation method based on correction learning. At first, a novel idea of correction learning is introduced.
Guang Zhang, Shuhao Dong, Hui Xu, Hongyu Zhang, Yongjian Wu 0001, Yanwei Zhang, Xiaoming Xi, Yilong Yin   +7 more
openaire   +2 more sources

Misperception of Body Weight After Childhood Cancer

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Misperception of body weight can negatively impact the weight management efforts of childhood cancer survivors (CCSs). Both being overweight or underweight are associated with chronic health conditions commonly observed in CCS; therefore, accurate weight perception is critical for reducing long‐term health risks.
Fabiën N. Belle, Tomáš Sláma, Eva Haegler‐Laube, Reto D. Kurmann, Gabriela M. Kuster, Christoph Saner, Eva Scheler, Yara Shoman, Christina Schindera   +8 more
wiley   +1 more source

Deep learning for medical image segmentation: State-of-the-art advancements and challenges

Informatics in Medicine Unlocked
Image segmentation, a crucial process of dividing images into distinct parts or objects, has witnessed remarkable advancements with the emergence of deep learning (DL) techniques. The use of layers in deep neural networks, like object form recognition in
Md. Eshmam Rayed, S.M. Sajibul Islam, Sadia Islam Niha, Jamin Rahman Jim, Md Mohsin Kabir, M.F. Mridha   +5 more
doaj   +1 more source

Medical Image Segmentation for Mobile Electronic Patient Charts Using Numerical Modeling of IoT

Journal of Applied Mathematics, 2014
Internet of Things (IoT) brings telemedicine a new chance. This enables the specialist to consult the patient’s condition despite the fact that they are in different places.
Seung-Hoon Chae, Daesung Moon, Deok Gyu Lee, Sung Bum Pan   +3 more
doaj   +1 more source

PENERAPAN CITRA TERKOMPRESI PADA SEGMENTASI CITRA MENGGUNAKAN ALGORITMA K-MEANS

JUTEI (Jurnal Terapan Teknologi Informasi), 2018
In the development of an image not only as a documentation of events. One area that requires image processing is in the field of medicine is radiology. In radiology there is a medical image required by doctors and researchers to be processed for patient ...
Angga Wijaya Kusuma, Rossy Lydia Ellyana
doaj   +1 more source

AutoSegNet: An Automated Neural Network for Image Segmentation

IEEE Access, 2020
Neural Architecture Search (NAS) has drawn significant attention as a tool for automatically constructing deep neural networks. The generated neural networks are mainly applied for image classification, and natural language processing. However, there are
Zhimin Xu, Si Zuo, Edmund Y. Lam, Byoungho Lee, Ni Chen   +4 more
doaj   +1 more source

Solid Pseudopapillary Neoplasm of the Pancreas in Children and Adolescents: Expert Recommendations

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Solid pseudopapillary neoplasm of the pancreas (SPN) is a rare low‐grade malignant exocrine pancreatic tumor, mostly discovered during the second decade of life in females, with a very good prognosis, provided microscopically complete surgical excision is achieved.
Sabine Irtan, Michael Abele, Calogero Virgone, Michaela Kuhlen, Ricardo Lopez‐Almarez, Tal Ben‐Ami, Ewa Bien, Maja Cesen, Malgorzata A. Krawczyk, Andrea Ferrari, Gianni Bisogno, Yves Reguerre, Dominik T. Schneider, Louise Galmiche, Jorg Fuchs, Sarah Braungart, Bilgehan Yalcin, Ines B. Brecht, Daniel Orbach   +18 more
wiley   +1 more source

Interactive Segmentation for Medical Images Using Spatial Modeling Mamba

Information
Interactive segmentation methods utilize user-provided positive and negative clicks to guide the model in accurately segmenting target objects. Compared to fully automatic medical image segmentation, these methods can achieve higher segmentation accuracy
Yuxin Tang, Yu Li, Hua Zou, Xuedong Zhang   +3 more
doaj   +1 more source

Impact of Metastatic Patterns on Survival and Response to Therapy in Neuroblastoma

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background While the presence of metastases in neuroblastoma (NB) is a well‐established prognostic factor, the clinical significance of dissemination patterns and tumour burden and their impact on response and survival remains poorly understood.
Mariona Morell‐Daniel, Santiago Pérez‐Hoyos, Aroa Soriano, Ana Coma, Amalia Varo, Raquel Hladun, Gabriela Guillén, Soraya Mico, Marta Garrido, Lourdes Rubio, Alba Rubio‐San‐Simón, Ana Minguez, Ricardo López‐Almaraz, Laura Illade, Miguel F. Segura, Lucas Moreno   +15 more
wiley   +1 more source