Results 61 to 70 of about 646,473 (271)
We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić+31 more
wiley +1 more source
Mammographic Image Enhancement using Digital Image Processing Technique [PDF]
Abstract PURPOSES this study aims to perform microcalsification detection by performing image enhancement in mammography image by using transformation of negative image and histogram equalization. image mammography with .pgm format changed to. jpg format then processed into negative image result then processed again using histogram equalization.
arxiv
Removing defocused objects from single focal plane scans of cytological slides
Background: Virtual microscopy and automated processing of cytological slides are more challenging compared to histological slides. Since cytological slides exhibit a three-dimensional surface and the required microscope objectives with high resolution ...
David Friedrich+3 more
doaj +1 more source
Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam+2 more
wiley +1 more source
A Review of Image Mosaicing Techniques [PDF]
Image Mosaicing is a method of constructing multiple images of the same scene into a larger image. The output of the image mosaic will be the union of two input images. Image-mosaicing algorithms are used to get mosaiced image. Image Mosaicing processed is basically divided in to 5 phases.
arxiv
Multi-Modality Image Inpainting using Generative Adversarial Networks [PDF]
Deep learning techniques, especially Generative Adversarial Networks (GANs) have significantly improved image inpainting and image-to-image translation tasks over the past few years. To the best of our knowledge, the problem of combining the image inpainting task with the multi-modality image-to-image translation remains intact.
arxiv
CIE L*a*b*: comparison of digital images obtained photographically by manual and automatic modes
The aim of this study was to analyze the color alterations performed by the CIE L*a*b* system in the digital imaging of shade guide tabs, which were obtained photographically according to the automatic and manual modes.
Fabiana Takatsui+4 more
doaj
This study simultaneously investigated circulating tumor cells (CTCs) and exosomes from small‐cell lung cancer (SCLC) patients. The elevated expression of JUNB and CXCR4 in CTCs was a poor prognostic factor for SCLC patients, whereas exosomal overexpression of these biomarkers revealed a high discrimination ability of patients from healthy individuals,
Dimitrios Papakonstantinou+13 more
wiley +1 more source
Image processing using miniKanren [PDF]
An integral image is one of the most efficient optimization technique for image processing. However an integral image is only a special case of delayed stream or memoization. This research discusses generalizing concept of integral image optimization technique, and how to generate an integral image optimized program code automatically from abstracted ...
arxiv
Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang+10 more
wiley +1 more source