The contributions of this thesis stem from technology developed to analyse large sets of volumetric images in terms of atom-like features extracted in 3D image space, following SIFT algorithm in 2D image space. New feature properties are introduced including a binary feature sign, analogous to an electrical charge, and a discrete set of symmetric feature orientation states in 3D space. These new properties are leveraged to extend feature invariance to include the sign inversion and parity (SP) transform, analogous to the charge conjugation and parity (CP) transform between a particle and its antiparticle in quantum mechanics, thereby accounting for local intensity contrast inversion between imaging modalities and axis reflections due to shape symmetry. A novel exponential kernel is proposed to quantify the similarity of a pair of features extracted in different images from their properties including location, scale, orientation, sign and appearance. A novel measure entitled the soft Jaccard is proposed to quantify the similarity of a pair of feature sets based on their overlap or intersection-over-union, where a kernel establishes non-binary or soft equivalence between a pair of feature elements. The soft Jaccard may be used to identify pairs of feature sets extracted from the same individuals or families with high accuracy, and a simple distance threshold led to the surprising discovery of previously unknown individual and family labeling errors in major public neuroimage datasets. A new algorithm is proposed to register or spatially align a pair of feature sets, entitled SIFT Coherent Point Drift (SIFT-CPD), by identifying a transform that maximizes the soft Jaccard between a fixed feature set and a transformed set. SIFT-CPD achieves faster and more accurate registration than the original CPD algorithm based on feature location information alone, in a variety of challenging.
翻译:该理论的贡献来自根据SIFT在 2D 图像空间的算法,在 3D 图像空间中根据3D 图像空间中提取的与原子相似的特性分析大批量图象的技术。 引入了新特性属性, 包括一个二进制特征符号, 类似于电荷, 以及一组离散的对称特征方向定位 3D 空间中。 这些新特性被利用以扩展特性的特性, 包括符号倒转和等( SP) 变异, 类似于粒子及其在量子力力学中的反射器变异( CP), 从而计算成像形式模式和轴反射轴反映之间的局部强度对比。 提议采用新型指数内置特征标志, 与其属性不同, 包括位置、 规模、 方向、 标志和外观。 软性Jaccar 提议采用新特征组合的变异性, 其根据重或交叉点对立( CP ), 内置内置软性或软性对立, 地( 软性) 硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性能特性, 的硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性硬性能能能能能能能性能能能能能能能能能能能能能性能能能能能能能能能能能能能能能能能能能能能能能能能能能能能能