肠病相关性T细胞淋巴瘤(enteropathy-associated T cell lymphoma,EATCL)是1985年Isaacson首先提出的起源于肠上皮内T淋巴细胞的恶性肿瘤。2002年WHO新分类对T细胞和NK细胞的淋巴组织肿瘤称为肠病型T细胞淋巴瘤(enteropathy type T c...肠病相关性T细胞淋巴瘤(enteropathy-associated T cell lymphoma,EATCL)是1985年Isaacson首先提出的起源于肠上皮内T淋巴细胞的恶性肿瘤。2002年WHO新分类对T细胞和NK细胞的淋巴组织肿瘤称为肠病型T细胞淋巴瘤(enteropathy type T cell lymphoma,ETTCL)。本病罕见,极易误诊,恶性程度高,预后极差,1年生存率不足30%,中位生存期为4个月。本文就我院收治的1例ETTCL患者的诊治经过,结合文献分析报道如下。展开更多
Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition sy...Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.展开更多
文摘肠病相关性T细胞淋巴瘤(enteropathy-associated T cell lymphoma,EATCL)是1985年Isaacson首先提出的起源于肠上皮内T淋巴细胞的恶性肿瘤。2002年WHO新分类对T细胞和NK细胞的淋巴组织肿瘤称为肠病型T细胞淋巴瘤(enteropathy type T cell lymphoma,ETTCL)。本病罕见,极易误诊,恶性程度高,预后极差,1年生存率不足30%,中位生存期为4个月。本文就我院收治的1例ETTCL患者的诊治经过,结合文献分析报道如下。
文摘Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it’s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.