DIGITAL mammographyDISEASE risk factorsBREAST cancerCONVOLUTIONAL neural networksDIGITAL learningBreast cancer remains the leading cause of cancer-related deaths in women worldwide. Current screening regimens and clinical breast cancer risk assessment models use risk factors such as demographics...
First, medical scanners are producing higher resolution digital images across modalities like MRI, CT, and PET [4]. Second, electronic health records now compile diverse clinical data in structured formats [5]. Finally, advanced analytics methods like deep learning are capable of modeling complex ...
The applications of these imaging systems range from medical applications like digital mammography or dental X-ray diagnostics to non destructive material ... C Schwarz,W Snoeys,KM Smith,... - Nuclear Physics B - Proceedings Supplements 被引量: 62发表: 1999年 X-ray pixel detector for crystallo...
It was suggested that the most cost-effective screening strategy in BRCA1 and BRCA2 mutation carriers may be an annual MRI beginning at age 25 years, with alternating MRI and digital mammography (so that each test is done annually but screening occurs every 6 months) beginning at age 30 ...
The proportion of cancers detectable for each modality was calculated. In 2023, Medicare reimbursement rates were used to estimate supplemental screening costs. Results Out of 469,437 detectable cancers, 2D mammography could detect 190,531 (41%), leaving 278,906 undetected. Adding supplemental ...
The average effective dose of 2-view film-screen mammography is 0.56 mSv and that of digital mammography is 0.44 mSv19. Therefore, this low-dose perfusion CT protocol is clinically applicable in terms of radiation exposure. If a flexible scan range customized for breast cancer size is ...
At the end of the experiment, rats were sacrificed and the left hind paws were radiographed with a digital mammography system (Planmed, Finland). Radiographs of ankle and tarsus joints of each rat were evaluated for bone destruction on a scale of 0 = normal, 1 = mild changes, 2 = modera...
A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nat Mach Intell. 2021;3(12):1061–70. Article Google Scholar Saleem H, Shahid AR, Raza B. Visual interpretability in 3d brain tumor segmentation network. Comput Biol Med. 2021;133:1044...
The most common imaging modalities consisting of mammography, ultrasound, MRI, thermography, CT, and biopsy are used as keyword to find the relevant papers. Based on the titles and abstracts, about 80 between 2016 and 2020 papers are selected and studied. The different sections of this study ...
The proposed algorithm has been tested on a number of images in Digital Database for Screening Mammography (DDSM), comparing the results with histogram equalization which is a well-established image enhancement technique and Cheng's enhancement algorithm based on wavelet transform. In order to ...