Subhamoy Mandal

About Subhamoy Mandal

Subhamoy Mandal, With an exceptional h-index of 13 and a recent h-index of 11 (since 2020), a distinguished researcher at Technische Universität München, specializes in the field of Medical Imaging, Medical Image Analysis, Augmented Reality, Biosignal Processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Speckle Noise Reduction in Ultrasound Images using Denoising Auto-encoder with Skip Connection

Memory replay for continual medical image segmentation through atypical sample selection

AR visualizations in laparoscopy: surgeon preferences and depth assessment of vascular anatomy

Phantom study on surgical performance in augmented reality laparoscopy

Boosting Algorithms based Cuff-less Blood Pressure Estimation from Clinically Relevant ECG and PPG Morphological Features

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics

Deep Learning based Skin-layer Segmentation for Characterizing Cutaneous Wounds from Optical Coherence Tomography Images

Apparatus and method for registering live and scan images

Subhamoy Mandal Information

University

Position

Maxer Endoscopy GmbH and

Citations(all)

573

Citations(since 2020)

351

Cited By

399

hIndex(all)

13

hIndex(since 2020)

11

i10Index(all)

16

i10Index(since 2020)

13

Email

University Profile Page

Google Scholar

Subhamoy Mandal Skills & Research Interests

Medical Imaging

Medical Image Analysis

Augmented Reality

Biosignal Processing

Top articles of Subhamoy Mandal

Speckle Noise Reduction in Ultrasound Images using Denoising Auto-encoder with Skip Connection

Bio-medical materials and engineering

2015/1/1

Memory replay for continual medical image segmentation through atypical sample selection

2023/10/1

AR visualizations in laparoscopy: surgeon preferences and depth assessment of vascular anatomy

Minimally Invasive Therapy & Allied Technologies

2023/8/1

Phantom study on surgical performance in augmented reality laparoscopy

International Journal of Computer Assisted Radiology and Surgery

2023/8

Boosting Algorithms based Cuff-less Blood Pressure Estimation from Clinically Relevant ECG and PPG Morphological Features

2023/7/24

Artificial Intelligence Assisted Multi-modal Photoacoustic-Ultrasound Imaging for Studying Renal Tissue Function and Hemodynamics

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

2023/7

Subhamoy Mandal
Subhamoy Mandal

H-Index: 12

Deep Learning based Skin-layer Segmentation for Characterizing Cutaneous Wounds from Optical Coherence Tomography Images

2023/7/24

Apparatus and method for registering live and scan images

2023/4/27

Endoscopic camera arrangement and method for camera alignment error correction

2023/4/27

Apparatus and method for positioning a patient's body and tracking the patient's position during surgery

2023/4/27

System and method for image registration

2023/4/27

Local Shape Preserving Deformations for Augmented Reality Assisted Laparoscopic Surgery

2022/7/11

Segmentation and Tracking of Tumor Vasculature Using Volumetric Multispectral Optoacoustic Tomography

2021/10/28

Subhamoy Mandal
Subhamoy Mandal

H-Index: 12

Noise adaptive beamforming for linear array photoacoustic imaging

IEEE Transactions on Instrumentation and Measurement

2021/8/9

Souradip Paul
Souradip Paul

H-Index: 3

Subhamoy Mandal
Subhamoy Mandal

H-Index: 12

Brilliant cresyl blue enhanced optoacoustic imaging enables non-destructive imaging of mammalian ovarian follicles for artificial reproduction

Journal of the Royal Society Interface

2020/11/25

Rahul Dutta
Rahul Dutta

H-Index: 12

Subhamoy Mandal
Subhamoy Mandal

H-Index: 12

Multiscale signal processing methods for improving image reconstruction and visual quality in led-based photoacoustic systems

LED-Based Photoacoustic Imaging: From Bench to Bedside

2020

Subhamoy Mandal
Subhamoy Mandal

H-Index: 12

See List of Professors in Subhamoy Mandal University(Technische Universität München)

Co-Authors

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