کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9387333 | 1281407 | 2005 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
How Can a Massive Training Artificial Neural Network (MTANN) Be Trained With a Small Number of Cases in the Distinction Between Nodules and Vessels in Thoracic CT?1
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کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت
پزشکی و دندانپزشکی
رادیولوژی و تصویربرداری
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: How Can a Massive Training Artificial Neural Network (MTANN) Be Trained With a Small Number of Cases in the Distinction Between Nodules and Vessels in Thoracic CT?1 How Can a Massive Training Artificial Neural Network (MTANN) Be Trained With a Small Number of Cases in the Distinction Between Nodules and Vessels in Thoracic CT?1](/preview/png/9387333.png)
چکیده انگلیسی
The MTANN can be trained with a very small number of training cases (10 nodules and 10 non-nodules) in the distinction between nodules and non-nodules (vessels) in CT images. Massive training by scanning of training cases to produce a large number of training samples (input subregions and teaching pixels) would contributed to a high generalization ability of the MTANN.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Academic Radiology - Volume 12, Issue 10, October 2005, Pages 1333-1341
Journal: Academic Radiology - Volume 12, Issue 10, October 2005, Pages 1333-1341
نویسندگان
Kenji Suzuki, Kunio Doi,