Results 91 to 100 of about 914,658 (364)
Intein‐based modular chimeric antigen receptor platform for specific CD19/CD20 co‐targeting
Molecular Oncology, EarlyView.CARtein is a modular CAR platform that uses split inteins to splice antigen‐recognition modules onto a universal signaling backbone, enabling precise, scarless assembly without re‐engineering signaling domains. Deployed here against CD19 and CD20 in B‐cell malignancies, the design supports flexible multi‐antigen targeting to boost T‐cell activation and
Pablo Gonzalez‐Garcia +9 more
wiley +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
International Research Journal on Advanced Engineering Hub (IRJAEH)Medical image segmentation is a critical component in the development of computer-aided diagnosis and treatment planning systems. This paper provides a comprehensive survey of recent advances in segmentation techniques applied to various imaging modalities, including Magnetic Resonance Imaging (MRI).
null Arpit Mohankar +4 more
openaire +1 more source
Molecular Oncology, EarlyView.Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source
A novel framework for segmentation of small targets in medical images
Scientific ReportsMedical image segmentation represents a pivotal and intricate procedure in the domain of medical image processing and analysis. With the progression of artificial intelligence in recent years, the utilization of deep learning techniques for medical image
Longxuan Zhao +10 more
doaj +1 more source
Medical image segmentation methods overview
Sistemnì Doslìdženâ ta Informacìjnì Tehnologìï, 2018 This article provides an overview of the modern medical image segmentation methods. The most popular methods such as multi-atlas based methods and deep learning approach are considered in more details.
Bohdan V. Chapaliuk, Yuriy P. Zaychenko
doaj +1 more source
AI in the Loop: functionalizing fold performance disagreement to monitor automated medical image segmentation workflows [PDF]
, 2023 Harrison C. Gottlich +3 more
openalex +1 more source
Molecular Oncology, EarlyView.HDAC4 is degraded by the E3 ligase FBXW7. In colorectal cancer, FBXW7 mutations prevent HDAC4 degradation, leading to oxaliplatin resistance. Forced degradation of HDAC4 using a PROTAC compound restores drug sensitivity by resetting the super‐enhancer landscape, reprogramming the epigenetic state of FBXW7‐mutated cells to resemble oxaliplatin ...
Vanessa Tolotto +13 more
wiley +1 more source
HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation [PDF]
IEEE Transactions on Medical ImagingMedical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discriminative; i.e., they aim to learn a mapping from the input image to ...
Tao Chen +4 more
semanticscholar +1 more source
Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source