Results 71 to 80 of about 488,489 (323)

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

open access: yesMolecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran   +16 more
wiley   +1 more source

Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model [PDF]

open access: yesarXiv, 2023
The Segment Anything Model (SAM) is a recently developed large model for general-purpose segmentation for computer vision tasks. SAM was trained using 11 million images with over 1 billion masks and can produce segmentation results for a wide range of objects in natural scene images.
arxiv  

Robust acute myeloid leukemia engraftment in humanized scaffolds using injectable biomaterials and intravenous xenotransplantation

open access: yesMolecular Oncology, EarlyView.
Patient‐derived xenografts (PDXs) can be improved by implantation of a humanized niche. We tested different biomaterials and approaches, and demonstrate that the combination of an injectable biomaterial for scaffold creation plus an intravenous route for acute myeloid leukemia (AML) xenotransplantation provide the most convenient and robust approach to
Daniel Busa   +13 more
wiley   +1 more source

Adaptive scale segmentation algorithm for polarimetric SAR image

open access: yesThe Journal of Engineering, 2019
Polarimetric SAR (PolSAR) data can be characterised by scattering matrix, which contains four elements. It is difficult to merge all the elements of the scattering matrix for segmentation.
Yifan Xu, Aifang Liu, Long Huang
doaj   +1 more source

Image Segmentation Algorithms Overview [PDF]

open access: yesarXiv, 2017
The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc.
arxiv  

Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer

open access: yesMolecular Oncology, EarlyView.
This study employed targeted metabolomic profiling to identify 302 distinct metabolites present in platelet‐rich plasma (PRP), revealing aberrant metabolic profiles amongst individuals diagnosed with colorectal cancer (CRC). Compared to carcinoembryonic antigen (CEA) and cancer antigen 19‐9 (CA199), our metabolite panel showed improved sensitivity ...
Zuojian Hu   +7 more
wiley   +1 more source

SRCNet: Seminal Representation Collaborative Network for Marine Oil Spill Segmentation [PDF]

open access: yesarXiv, 2023
Effective oil spill segmentation in Synthetic Aperture Radar (SAR) images is critical for marine oil pollution cleanup, and proper image representation is helpful for accurate image segmentation. In this paper, we propose an effective oil spill image segmentation network named SRCNet by leveraging SAR image representation and the training for oil spill
arxiv  

TRPM4 contributes to cell death in prostate cancer tumor spheroids, and to extravasation and metastasis in a zebrafish xenograft model system

open access: yesMolecular Oncology, EarlyView.
Transient receptor potential melastatin‐4 (TRPM4) is overexpressed in prostate cancer (PCa). Knockout of TRPM4 resulted in reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids.
Florian Bochen   +6 more
wiley   +1 more source

Lung image segmentation via generative adversarial networks

open access: yesFrontiers in Physiology
IntroductionLung image segmentation plays an important role in computer-aid pulmonary disease diagnosis and treatment.MethodsThis paper explores the lung CT image segmentation method by generative adversarial networks.
Jiaxin Cai   +4 more
doaj   +1 more source

Response to neoadjuvant chemotherapy in early breast cancers is associated with epithelial–mesenchymal transition and tumor‐infiltrating lymphocytes

open access: yesMolecular Oncology, EarlyView.
Epithelial–mesenchymal transition (EMT) and tumor‐infiltrating lymphocytes (TILs) are associated with early breast cancer response to neoadjuvant chemotherapy (NAC). This study evaluated EMT and TIL shifts, with immunofluorescence and RNA sequencing, at diagnosis and in residual tumors as potential biomarkers associated with treatment response.
Françoise Derouane   +16 more
wiley   +1 more source

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