找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Digital Mammography; IWDM 2002 — 6th Inte Heinz-Otto Peitgen (Professor of Mathematics and B Conference proceedings 2003 Springer-Verlag Be

[復(fù)制鏈接]
樓主: 警察在苦笑
51#
發(fā)表于 2025-3-30 08:39:41 | 只看該作者
Evaluation of light collection in digital indirect detection x-ray imagers: Monte Carlo simulations ly below the x-ray interaction point and 41% in the 8 nearest neighbor pixels) was collected by the photodetector for Imager 2 compared with only 56% (28% in the central pixel and 28% by the nearest neighbor pixels) for Imager 1.
52#
發(fā)表于 2025-3-30 15:47:25 | 只看該作者
53#
發(fā)表于 2025-3-30 19:22:16 | 只看該作者
54#
發(fā)表于 2025-3-30 23:39:47 | 只看該作者
Communications and Control Engineeringn Rose’s criterion (SNR≥5), that breast CT can produce excellent image quality at mean glandular doses comparable to mammography. The potential to identify smaller lesions may improve early detection performance, which in turn would likely result in a reduction of breast cancer mortality.
55#
發(fā)表于 2025-3-31 02:54:40 | 只看該作者
56#
發(fā)表于 2025-3-31 07:30:10 | 只看該作者
Digital mammographic application of a single photon counting pixel detectorick a matrix of 64 x 64 square pixels with a dimension side of 170 μm. The active area is about 1.2 cm.. The photon counting chip matches the geometry of the detector so it has 4096 asynchronous read-out cells, each containing a charge preamplifier, a leading edge comparator and a pseudorandom count
57#
發(fā)表于 2025-3-31 11:47:50 | 只看該作者
58#
發(fā)表于 2025-3-31 16:19:08 | 只看該作者
59#
發(fā)表于 2025-3-31 18:51:05 | 只看該作者
Digital Mammography vs. Screen-Film Mammography: a Phantom Studyuji imaging plates system (photostimulable phosphors, 50 micron pixel size), implemented on a conventional mammography unit. We conducted a first comparison between laser printed images and 4 different high contrast conventional screen-film combinations. Three specific mammographic phantoms were use
60#
發(fā)表于 2025-3-31 22:59:02 | 只看該作者
Mammography Taxonomy for the Improvement of Lesion Detection Ratesh automatically classifies breast parenchyma. The classification engine is an artificial neural network which successfully forms narrow classes to capture the subtleties in parenchyma variation. This paper presents the result of a series of experiments that digitized 628 mammograms at 50 μm from the
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-17 00:26
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
台安县| 株洲市| 茂名市| 保定市| 肇源县| 沂水县| 株洲县| 海门市| 马尔康县| 舒城县| 洱源县| 五指山市| 宜昌市| 广灵县| 嘉黎县| 连云港市| 城步| 大渡口区| 怀化市| 和林格尔县| 白城市| 额敏县| 马龙县| 海城市| 株洲县| 长沙市| 秦安县| 汪清县| 富裕县| 彰武县| 筠连县| 滨州市| 稻城县| 黑龙江省| 怀来县| 桐庐县| 于都县| 雷州市| 宁阳县| 沐川县| 广州市|