Localization of Microcalcification on the Mammogram Using Deep Convolutional Neural Network

Breast cancer is the most common cancer in women worldwide, and the mammogram is the most widely used screening technique for breast cancer. To make a diagnosis in the early stage of breast cancer, the appearance of masses and microcalcifications on the mammogram are two crucial indicators. Notably, the early detection of malignant microcalcifications can facilitate the diagnosis and the treatment of breast cancer at the appropriate time. Making an accurate evaluation on microcalcifications is a timeconsuming and challenging task for the radiologists due to the small size and the low contrast of microcalcification. Compared to the background and mammogram image with noises, it is tough to be discriminated. Computer-Aided Detection (CADe) have been deployed to support radiologists. However, most of current CADe systems need to have hand-crafted image features to be implemented. For improvement in the conventional approach, Convolutional Neural Network (CNN) with no hand-crafted image feature is used in this thesis. CNN with Class Activation Map (CAM) is deployed to implement the microcalcification detection in mammograms. GoogLeNet architecture with nine inception modules and one CAM layer is used to improve the localization capability of GoogLeNet in microcalcification detection while maintaining the local information. The network is trained and tested with Curated Breast Imaging Subset of Digital Database for Screening Mammography dataset (CBIS-DDSM). This approach demonstrates that the localization ability of CAM for abnormal microcalcification regions on the mammogram can be improved by restoring the last two inception modules that were removed in the paper [1] [16]. For the CAM, CAM layer is inserted in the position of the second auxiliary layer that was used in the original GoogLeNet [17] for training. This allowed us to use the intermediate feature at the same location from [1] [16] for localization while maintaining the depth of the GoogLeNet [17]. The experimental result shows that this method achieved about 225.15% better result at localizing microcalcification in mammograms than the existing method

Vocal Flexibility in Early Human Communication

The dissertation contains two papers on the theme of flexibility in infant communication using an infrastructural approach. An infrastructural approach considers infant communication in terms of properties of human language (i.e., spontaneous vocalization, functional flexibility, social interactivity, and etc.). Infants\u27 vocal flexibility is explored in two ways in the dissertation: 1) How infants use sounds with varying emotional valences, a primary determiner of their communicative functions, and when this infrastrucutral property emerges (the first paper, in Chapter 2), and 2) what role the voice plays independently and jointly with the face in the transmission of affect and vocal type (the second paper, in Chapter 3). The first paper demonstrates that infants explore vocalizations in protophones and associate them with a range of affect as early as the first month of life. That is, all the protophone types we examined showed strong functional flexibility by showing significantly more neutral facial affect than cry and significantly less negative facial affect than cry. Further, infant protophones were functionally flexible across all three months, being differentiated from cry at all the ages. The second study revealed an important distinction in the use of face and voice in affect vs. protophone expression. Affect was transmitted with audio and video being flexibly interwoven, suggesting infant vocal capabilities establish a foundation for the flexible use of the voice, as is required in language. Both works contribute to our understanding of the path leading to the infants\u27 speech capacity

Model Studies on Rare Earth Oxide Thin Films : Surface Chemistry and Catalytic Properties

Rare earth oxides (REOs) have shown considerable capacities for performing certain catalytic reactions. However, only ceria (CeOx) has been systematically studied regarding the surface chemistry and the factors for catalytic behavior. The fundamental understanding with respect to the connections between the surface chemistry and catalytic properties of other REOs is still in a very limited scope. Major part of this PhD dissertation reports on surface science studies of samaria (SmOx) conducted in ultra-high vacuum. In addition, the dissertation briefly introduces recent studies on praseodymia (PrOx), PrOx-CeOx mixed oxides, and terbia (TbOx) which were carried out by my working group (AG Bäumer) and our collaborators. Sm2O3 thin films grown on a Pt(111) substrate were employed as SmOx model systems. Structural and film morphologic studies were conducted by low-energy electron diffraction (LEED) and scanning tunneling microscopy (STM). Such thin films grow as a defective-fluorite structure, i.e., Sm atoms arrange into a hexagonal sublattice whereas surface vacancies randomly distribute on the thin films. A film wetting/dewetting behavior responding to the SmOx reduction/oxidation conditions was observed. To learn about the chemical/catalytic properties of the SmOx model system, carbon monoxide (CO), water (D2O), and methanol (MeOH) were dosed onto the system for adsorption-reaction experiments conducted by temperature programmed desorption spectroscopy (TPD). The MeOH-TPD study was further combined with infrared absorption-reflection spectroscopy (IRRAS) to gain the whole picture of the MeOH reaction mechanism on the model system. The influence of the SmOx reduction/oxidation conditions on the chemical responses of these adsorbates were also investigated. The existence of the perimeter sites between SmOx islands and uncovered Pt areas obviously promotes the reactivity and alters chemical properties of the SmOx model system. A spillover of adsorbed species from the SmOx surface to exposed Pt areas was observed. It is particularly important in increasing the SmOx reactivity towards the MeOH decomposition

Direct observation of band-gap closure for a semiconducting carbon nanotube in a large parallel magnetic field

We have investigated the magnetoconductance of semiconducting carbon nanotubes (CNTs) in pulsed, parallel magnetic fields up to 60 T, and report the direct observation of the predicted band-gap closure and the reopening of the gap under variation of the applied magnetic field. We also highlight the important influence of mechanical strain on the magnetoconductance of the CNTs.Comment: 4 pages, 4 figure