Takahiro Nakao

16 papers Journal 16

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Detection of pulmonary nodules in chest radiographs: novel cost function for effective network training with purely synthesized datasets. Int. J. Comput. Assist. Radiol. Surg. Shouhei Hanaoka, Yukihiro Nomura, Takeharu Yoshikawa, Takahiro Nakao, Tomomi Takenaga, Hirotaka Matsuzaki, Nobutake Yamamichi, Osamu Abe
2024	J	`jnl`	Improved identification of tumors in 18F-FDG-PET examination by normalizing the standard uptake in the liver based on blood test data. Int. J. Comput. Assist. Radiol. Surg. Md. Ashraful Alam, Shouhei Hanaoka, Yukihiro Nomura, Tomohiro Kikuchi, Takahiro Nakao, Tomomi Takenaga, Naoto Hayashi, Takeharu Yoshikawa, Osamu Abe
2024	J	`jnl`	Performance changes due to differences among annotating radiologists for training data in computerized lesion detection. Int. J. Comput. Assist. Radiol. Surg. Yukihiro Nomura, Shouhei Hanaoka, Naoto Hayashi, Takeharu Yoshikawa, Saori Koshino, Chiaki Sato, Momoko Tatsuta, Yuya Tanaka, Shintaro Kano, Moto Nakaya, Shohei Inui, Masashi Kusakabe, Takahiro Nakao, Soichiro Miki, Takeyuki Watadani, Ryusuke Nakaoka, Akinobu Shimizu, Osamu Abe
2024	J	`jnl`	Synthesis of Hybrid Data Consisting of Chest Radiographs and Tabular Clinical Records Using Dual Generative Models for COVID-19 Positive Cases. J. Imaging Inform. Medicine Tomohiro Kikuchi, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Yukihiro Nomura, Harushi Mori, Takeharu Yoshikawa
2024	J	`jnl`	Zero-shot 3D Segmentation of Abdominal Organs in CT Scans Using Segment Anything Model 2: Adapting Video Tracking Capabilities for 3D Medical Imaging. CoRR Yosuke Yamagishi, Shouhei Hanaoka, Tomohiro Kikuchi, Takahiro Nakao, Yuta Nakamura, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Osamu Abe
2023	J	`jnl`	Synthetic data generation method for hybrid image-tabular data using two generative adversarial networks. CoRR Tomohiro Kikuchi, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Yukihiro Nomura, Harushi Mori, Takeharu Yoshikawa
2021	J	`jnl`	Automatic detection of actionable radiology reports using bidirectional encoder representations from transformers. BMC Medical Informatics Decis. Mak. Yuta Nakamura, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Soichiro Miki, Takeyuki Watadani, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2021	J	`jnl`	Multichannel three-dimensional fully convolutional residual network-based focal liver lesion detection and classification in Gd-EOB-DTPA-enhanced MRI. Int. J. Comput. Assist. Radiol. Surg. Tomomi Takenaga, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Hisaichi Shibata, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2021	J	`jnl`	Preliminary study of generalized semiautomatic segmentation for 3D voxel labeling of lesions based on deep learning. Int. J. Comput. Assist. Radiol. Surg. Yukihiro Nomura, Shouhei Hanaoka, Tomomi Takenaga, Takahiro Nakao, Hisaichi Shibata, Soichiro Miki, Takeharu Yoshikawa, Takeyuki Watadani, Naoto Hayashi, Osamu Abe
2021	J	`jnl`	Unsupervised Deep Anomaly Detection in Chest Radiographs. J. Digit. Imaging Takahiro Nakao, Shouhei Hanaoka, Yukihiro Nomura, Masaki Murata, Tomomi Takenaga, Soichiro Miki, Takeyuki Watadani, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2021	J	`jnl`	Versatile anomaly detection method for medical images with semi-supervised flow-based generative models. Int. J. Comput. Assist. Radiol. Surg. Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Issei Sato, Daisuke Sato, Naoto Hayashi, Osamu Abe
2021	J	`jnl`	X2CT-FLOW: Reconstruction of multiple volumetric chest computed tomography images with different likelihoods from a uni- or biplanar chest X-ray image using a flow-based generative model. CoRR Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Tomomi Takenaga, Naoto Hayashi, Osamu Abe
2020	J	`jnl`	Anomaly detection in chest radiographs with a weakly supervised flow-based deep learning method. CoRR Hisaichi Shibata, Shouhei Hanaoka, Yukihiro Nomura, Takahiro Nakao, Issei Sato, Naoto Hayashi, Osamu Abe
2020	J	`jnl`	Development of training environment for deep learning with medical images on supercomputer system based on asynchronous parallel Bayesian optimization. J. Supercomput. Yukihiro Nomura, Issei Sato, Toshihiro Hanawa, Shouhei Hanaoka, Takahiro Nakao, Tomomi Takenaga, Tetsuya Hoshino, Yuji Sekiya, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2019	J	`jnl`	Four-dimensional fully convolutional residual network-based liver segmentation in Gd-EOB-DTPA-enhanced MRI. Int. J. Comput. Assist. Radiol. Surg. Tomomi Takenaga, Shouhei Hanaoka, Yukihiro Nomura, Mitsutaka Nemoto, Masaki Murata, Takahiro Nakao, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe
2019	J	`jnl`	HoTPiG: a novel graph-based 3-D image feature set and its applications to computer-assisted detection of cerebral aneurysms and lung nodules. Int. J. Comput. Assist. Radiol. Surg. Shouhei Hanaoka, Yukihiro Nomura, Tomomi Takenaga, Masaki Murata, Takahiro Nakao, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe, Akinobu Shimizu

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.