Results 31 to 40 of about 151,110 (308)
Pixel Diffuser: Practical Interactive Medical Image Segmentation without Ground Truth
Bioengineering, 2023 Medical image segmentation is essential for doctors to diagnose diseases and manage patient status. While deep learning has demonstrated potential in addressing segmentation challenges within the medical domain, obtaining a substantial amount of data ...
Mingeon Ju +5 more
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Current Directions in Biomedical Engineering, 2017 Multimodal imaging is gaining in importance in the field of personalized medicine and can be described as a current trend in medical imaging diagnostics. The segmentation, classification and analysis of tissue structures is essential.
Stich Manuel +3 more
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Application of Image Segmentation Technology Based on Machine Learning in Medical Image Analysis [PDF]
ITM Web of ConferencesMedical image analysis heavily relies on the crucial step of image segmentation, which possesses the capability to discern and differentiate various structures within medical imagery.
Zhang Yurun
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Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition
Sensors, 2023 This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing breast
Deawon Kwak, Jiwoo Choi, Sungjin Lee
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Ongoing evidence indicates increased risk of sarcopenic obesity among children and young people (CYP) with acute lymphoblastic leukemia (ALL), often beginning early in treatment, persisting into survivorship. This review evaluates current literature on body composition in CYP with ALL during and after treatment.
Lina A. Zahed +5 more
wiley +1 more source
Parent‐to‐Child Information Disclosure in Pediatric Oncology
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor +12 more
wiley +1 more source
A review: Deep learning for medical image segmentation using multi-modality fusion
Array, 2019 Multi-modality is widely used in medical imaging, because it can provide multiinformation about a target (tumor, organ or tissue). Segmentation using multimodality consists of fusing multi-information to improve the segmentation.
Tongxue Zhou, Su Ruan, Stéphane Canu
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Sensors, 2022 The latest medical image segmentation methods uses UNet and transformer structures with great success. Multiscale feature fusion is one of the important factors affecting the accuracy of medical image segmentation. Existing transformer-based UNet methods
Shaolong Chen +3 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background B‐acute lymphoblastic leukemia (B‐ALL) is the most common pediatric cancer, and while most children in high‐resource settings are cured, therapy carries risks for long‐term toxicities. Understanding parents’ concerns about these late effects is essential to guide anticipatory support and inform evolving therapeutic approaches ...
Kellee N. Parker +7 more
wiley +1 more source
Distributed contrastive learning for medical image segmentation
Medical Image Analysis, 2022 arXiv admin note: substantial text overlap with arXiv:2204 ...
Yawen Wu +4 more
openaire +3 more sources