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    • 1. 发明申请
    • AUTOMATED DETECTION OF MELANOMA
    • 自动检测梅拉诺马
    • WO2011031879A3
    • 2011-06-23
    • PCT/US2010048296
    • 2010-09-09
    • UNIV OREGON HEALTH & SCIENCEGAREAU DANHENNESSY RICKYJACQUES STEVE
    • GAREAU DANHENNESSY RICKYJACQUES STEVE
    • G06T7/00G06T17/00
    • G06T7/0057G06K9/00147G06T7/521G06T7/70G06T2207/10056G06T2207/30088G06T2207/30096
    • Embodiments herein exploit the optical sectioning capability of reflectance confocal microscopy to non-invasively survey the dermal-epidermal junction (DEJ), noting the irregularities associated with malignancy. Methods are provided to aid a clinician in diagnosing melanoma through pattern recognition to extract pertinent diagnostic information from large 3D confocal images. Identifying the combination of pagetoid melanocytes and DEJ breakdown increases the accuracy of detection. A method may be used to process a 3D confocal volume of images taken by a clinician of a suspicious lesion and deduce the depth location z of the first reflective surface (FRS) at each x-y position. This FRS is where the most superficial melanin resides. In this manner, the stratum corneum and epidermis are digitally stripped and no longer distract the clinician from the more diagnostically relevant pigmented cell network. The FRS is putatively either the DEJ for benign nevi or the depth of a pagetoid melanocyte at x,y above the DEJ. Thus by creating a 3D surface plot of the FRS for each lateral x,y point, the presence of pagetoid cells is identified by a discreet jump in the FRS above the level of the DEJ. The DEJ map may also be used to determine if breakdown of the DEJ is occurring.
    • 本文的实施例利用反射共焦显微镜的光学切片能力来非侵入性地调查真皮 - 表皮结合部(DEJ),注意与恶性肿瘤相关的不规则性。 提供方法来帮助临床医师通过模式识别来诊断黑素瘤以从大型3D共焦图像中提取相关的诊断信息。 识别页面黑素细胞和DEJ分解的组合提高了检测的准确性。 可以使用一种方法来处理可疑病变的临床医生拍摄的3D共焦区图像,并且推导第一反射表面(FRS)在每个x-y位置处的深度位置z。 这FRS是最肤浅的黑色素居住的地方。 以这种方式,角质层和表皮被数字剥离并且不再分散临床医师与更多诊断相关的色素沉着细胞网络。 FRS推定为DEJ为良性痣或深度为pageyid黑素细胞的x,y高于DEJ。 因此,通过为每个横向x,y点创建FRS的3D表面图,通过在DEJ水平之上的FRS中的离散跳跃来识别页面单元格的存在。 DEJ图也可用于确定DEJ是否发生故障。
    • 2. 发明申请
    • AUTOMATED DETECTION OF MELANOMA
    • 自动检测MELANOMA
    • WO2011031879A2
    • 2011-03-17
    • PCT/US2010/048296
    • 2010-09-09
    • OREGON HEALTH & SCIENCE UNIVERSITYGAREAU, DanHENNESSY, RickyJACQUES, Steve
    • GAREAU, DanHENNESSY, RickyJACQUES, Steve
    • G06T7/00G06T17/00
    • G06T7/0057G06K9/00147G06T7/521G06T7/70G06T2207/10056G06T2207/30088G06T2207/30096
    • Embodiments herein exploit the optical sectioning capability of reflectance confocal microscopy to non-invasively survey the dermal-epidermal junction (DEJ), noting the irregularities associated with malignancy. Methods are provided to aid a clinician in diagnosing melanoma through pattern recognition to extract pertinent diagnostic information from large 3D confocal images. Identifying the combination of pagetoid melanocytes and DEJ breakdown increases the accuracy of detection. A method may be used to process a 3D confocal volume of images taken by a clinician of a suspicious lesion and deduce the depth location z of the first reflective surface (FRS) at each x-y position. This FRS is where the most superficial melanin resides. In this manner, the stratum corneum and epidermis are digitally stripped and no longer distract the clinician from the more diagnostically relevant pigmented cell network. The FRS is putatively either the DEJ for benign nevi or the depth of a pagetoid melanocyte at x,y above the DEJ. Thus by creating a 3D surface plot of the FRS for each lateral x,y point, the presence of pagetoid cells is identified by a discreet jump in the FRS above the level of the DEJ. The DEJ map may also be used to determine if breakdown of the DEJ is occurring.
    • 本文的实施例利用反射共聚焦显微镜的光学切片能力来非侵入性地测量皮肤 - 表皮连接处(DEJ),注意到与恶性肿瘤相关的不规则性。 提供方法以帮助临床医师通过模式识别来诊断黑素瘤,以从大的3D共焦图像中提取相关的诊断信息。 识别网页黑素细胞和DEJ分解的组合增加了检测的准确性。 可以使用一种方法来处理由临床医生拍摄的可疑病变的3D共焦体积,并在每个x-y位置推导第一反射表面(FRS)的深度位置z。 这种FRS是最肤浅的黑色素所在。 以这种方式,角质层和表皮被数字剥离,并且不再使临床医师从更诊断性的相关色素细胞网络分散注意力。 FRS推定为DEJ用于良性痣或在DEJ上方的x,y处的网页黑素细胞的深度。 因此,通过为每个横向x,y点创建FRS的3D曲面图,通过在DEJ的水平之上的FRS中的谨慎跳跃来识别网页细胞的存在。 也可以使用DEJ图来确定DEJ的故障是否发生。